Pandas Profiling Report

Dataset statistics

Number of variables	79
Number of observations	50
Missing cells	1389
Missing cells (%)	35.2%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	31.0 KiB
Average record size in memory	634.6 B

Variable types

Numeric	6
Categorical	67
Unsupported	2
Boolean	4

Alerts

`ResponseId` is highly overall correlated with `TBranch`	High correlation
`YearsCode` is highly overall correlated with `YearsCodePro` and 3 other fields	High correlation
`YearsCodePro` is highly overall correlated with `YearsCode` and 10 other fields	High correlation
`CompTotal` is highly overall correlated with `WorkExp` and 10 other fields	High correlation
`WorkExp` is highly overall correlated with `YearsCode` and 16 other fields	High correlation
`ConvertedCompYearly` is highly overall correlated with `YearsCodePro` and 12 other fields	High correlation
`MainBranch` is highly overall correlated with `RemoteWork` and 4 other fields	High correlation
`Employment` is highly overall correlated with `RemoteWork` and 7 other fields	High correlation
`RemoteWork` is highly overall correlated with `MainBranch` and 7 other fields	High correlation
`CodingActivities` is highly overall correlated with `ConvertedCompYearly` and 5 other fields	High correlation
`EdLevel` is highly overall correlated with `LanguageHaveWorkedWith`	High correlation
`LearnCode` is highly overall correlated with `WorkExp` and 2 other fields	High correlation
`LearnCodeOnline` is highly overall correlated with `LearnCodeCoursesCert` and 18 other fields	High correlation
`LearnCodeCoursesCert` is highly overall correlated with `CompTotal` and 30 other fields	High correlation
`DevType` is highly overall correlated with `LearnCodeCoursesCert` and 7 other fields	High correlation
`OrgSize` is highly overall correlated with `LearnCodeCoursesCert` and 8 other fields	High correlation
`PurchaseInfluence` is highly overall correlated with `LanguageHaveWorkedWith` and 3 other fields	High correlation
`BuyNewTool` is highly overall correlated with `WorkExp` and 4 other fields	High correlation
`Country` is highly overall correlated with `CodingActivities` and 6 other fields	High correlation
`Currency` is highly overall correlated with `Employment` and 8 other fields	High correlation
`CompFreq` is highly overall correlated with `CompTotal` and 8 other fields	High correlation
`LanguageHaveWorkedWith` is highly overall correlated with `YearsCode` and 56 other fields	High correlation
`LanguageWantToWorkWith` is highly overall correlated with `WorkExp` and 13 other fields	High correlation
`DatabaseHaveWorkedWith` is highly overall correlated with `Employment` and 7 other fields	High correlation
`DatabaseWantToWorkWith` is highly overall correlated with `LanguageHaveWorkedWith` and 9 other fields	High correlation
`PlatformHaveWorkedWith` is highly overall correlated with `LearnCodeOnline` and 10 other fields	High correlation
`PlatformWantToWorkWith` is highly overall correlated with `YearsCodePro` and 22 other fields	High correlation
`WebframeHaveWorkedWith` is highly overall correlated with `YearsCodePro` and 30 other fields	High correlation
`WebframeWantToWorkWith` is highly overall correlated with `YearsCodePro` and 40 other fields	High correlation
`MiscTechHaveWorkedWith` is highly overall correlated with `MainBranch` and 13 other fields	High correlation
`MiscTechWantToWorkWith` is highly overall correlated with `Employment` and 17 other fields	High correlation
`ToolsTechHaveWorkedWith` is highly overall correlated with `WorkExp` and 8 other fields	High correlation
`ToolsTechWantToWorkWith` is highly overall correlated with `DevType` and 6 other fields	High correlation
`NEWCollabToolsHaveWorkedWith` is highly overall correlated with `LanguageHaveWorkedWith` and 3 other fields	High correlation
`NEWCollabToolsWantToWorkWith` is highly overall correlated with `LearnCodeOnline` and 3 other fields	High correlation
`OpSysProfessional use` is highly overall correlated with `LanguageHaveWorkedWith` and 2 other fields	High correlation
`OpSysPersonal use` is highly overall correlated with `ICorPM` and 1 other fields	High correlation
`VersionControlSystem` is highly overall correlated with `WorkExp` and 19 other fields	High correlation
`VCInteraction` is highly overall correlated with `LanguageHaveWorkedWith` and 3 other fields	High correlation
`OfficeStackAsyncHaveWorkedWith` is highly overall correlated with `ConvertedCompYearly` and 10 other fields	High correlation
`OfficeStackAsyncWantToWorkWith` is highly overall correlated with `MainBranch` and 14 other fields	High correlation
`OfficeStackSyncHaveWorkedWith` is highly overall correlated with `RemoteWork` and 6 other fields	High correlation
`OfficeStackSyncWantToWorkWith` is highly overall correlated with `RemoteWork` and 11 other fields	High correlation
`Blockchain` is highly overall correlated with `ICorPM` and 1 other fields	High correlation
`NEWSOSites` is highly overall correlated with `Frequency_1`	High correlation
`SOAccount` is highly overall correlated with `MiscTechHaveWorkedWith` and 4 other fields	High correlation
`SOPartFreq` is highly overall correlated with `WebframeWantToWorkWith` and 3 other fields	High correlation
`SOComm` is highly overall correlated with `Frequency_1` and 1 other fields	High correlation
`Age` is highly overall correlated with `YearsCode` and 3 other fields	High correlation
`Gender` is highly overall correlated with `LearnCodeCoursesCert` and 13 other fields	High correlation
`Trans` is highly overall correlated with `YearsCodePro` and 45 other fields	High correlation
`Sexuality` is highly overall correlated with `Employment` and 7 other fields	High correlation
`Ethnicity` is highly overall correlated with `LanguageHaveWorkedWith` and 3 other fields	High correlation
`Accessibility` is highly overall correlated with `LearnCodeCoursesCert` and 11 other fields	High correlation
`MentalHealth` is highly overall correlated with `LearnCodeOnline` and 5 other fields	High correlation
`TBranch` is highly overall correlated with `ResponseId` and 23 other fields	High correlation
`ICorPM` is highly overall correlated with `YearsCodePro` and 25 other fields	High correlation
`Knowledge_1` is highly overall correlated with `LanguageHaveWorkedWith` and 7 other fields	High correlation
`Knowledge_2` is highly overall correlated with `LanguageHaveWorkedWith` and 7 other fields	High correlation
`Knowledge_3` is highly overall correlated with `LearnCodeOnline` and 11 other fields	High correlation
`Knowledge_4` is highly overall correlated with `LearnCodeOnline` and 9 other fields	High correlation
`Knowledge_5` is highly overall correlated with `LanguageHaveWorkedWith` and 6 other fields	High correlation
`Knowledge_6` is highly overall correlated with `LearnCodeOnline` and 8 other fields	High correlation
`Knowledge_7` is highly overall correlated with `LearnCodeOnline` and 10 other fields	High correlation
`Frequency_1` is highly overall correlated with `CompTotal` and 18 other fields	High correlation
`Frequency_2` is highly overall correlated with `LearnCodeOnline` and 11 other fields	High correlation
`Frequency_3` is highly overall correlated with `MainBranch` and 10 other fields	High correlation
`TimeSearching` is highly overall correlated with `Country` and 10 other fields	High correlation
`TimeAnswering` is highly overall correlated with `CompTotal` and 14 other fields	High correlation
`Onboarding` is highly overall correlated with `LearnCodeOnline` and 12 other fields	High correlation
`ProfessionalTech` is highly overall correlated with `LearnCodeCoursesCert` and 10 other fields	High correlation
`TrueFalse_1` is highly overall correlated with `LanguageHaveWorkedWith` and 9 other fields	High correlation
`TrueFalse_2` is highly overall correlated with `LearnCodeCoursesCert` and 8 other fields	High correlation
`TrueFalse_3` is highly overall correlated with `YearsCodePro` and 13 other fields	High correlation
`SurveyLength` is highly overall correlated with `OfficeStackAsyncWantToWorkWith` and 1 other fields	High correlation
`SurveyEase` is highly overall correlated with `OpSysPersonal use` and 1 other fields	High correlation
`VersionControlSystem` is highly imbalanced (70.6%)	Imbalance
`Gender` is highly imbalanced (57.1%)	Imbalance
`Trans` is highly imbalanced (74.3%)	Imbalance
`Accessibility` is highly imbalanced (72.9%)	Imbalance
`ICorPM` is highly imbalanced (67.7%)	Imbalance
`Employment` has 2 (4.0%) missing values	Missing
`RemoteWork` has 12 (24.0%) missing values	Missing
`CodingActivities` has 12 (24.0%) missing values	Missing
`EdLevel` has 3 (6.0%) missing values	Missing
`LearnCode` has 4 (8.0%) missing values	Missing
`LearnCodeOnline` has 17 (34.0%) missing values	Missing
`LearnCodeCoursesCert` has 39 (78.0%) missing values	Missing
`YearsCode` has 3 (6.0%) missing values	Missing
`YearsCodePro` has 17 (34.0%) missing values	Missing
`DevType` has 12 (24.0%) missing values	Missing
`OrgSize` has 17 (34.0%) missing values	Missing
`PurchaseInfluence` has 17 (34.0%) missing values	Missing
`BuyNewTool` has 5 (10.0%) missing values	Missing
`Country` has 2 (4.0%) missing values	Missing
`Currency` has 16 (32.0%) missing values	Missing
`CompTotal` has 26 (52.0%) missing values	Missing
`CompFreq` has 24 (48.0%) missing values	Missing
`LanguageHaveWorkedWith` has 4 (8.0%) missing values	Missing
`LanguageWantToWorkWith` has 5 (10.0%) missing values	Missing
`DatabaseHaveWorkedWith` has 12 (24.0%) missing values	Missing
`DatabaseWantToWorkWith` has 18 (36.0%) missing values	Missing
`PlatformHaveWorkedWith` has 22 (44.0%) missing values	Missing
`PlatformWantToWorkWith` has 30 (60.0%) missing values	Missing
`WebframeHaveWorkedWith` has 17 (34.0%) missing values	Missing
`WebframeWantToWorkWith` has 22 (44.0%) missing values	Missing
`MiscTechHaveWorkedWith` has 24 (48.0%) missing values	Missing
`MiscTechWantToWorkWith` has 30 (60.0%) missing values	Missing
`ToolsTechHaveWorkedWith` has 20 (40.0%) missing values	Missing
`ToolsTechWantToWorkWith` has 24 (48.0%) missing values	Missing
`NEWCollabToolsHaveWorkedWith` has 3 (6.0%) missing values	Missing
`NEWCollabToolsWantToWorkWith` has 9 (18.0%) missing values	Missing
`OpSysProfessional use` has 6 (12.0%) missing values	Missing
`OpSysPersonal use` has 2 (4.0%) missing values	Missing
`VersionControlSystem` has 2 (4.0%) missing values	Missing
`VCInteraction` has 5 (10.0%) missing values	Missing
`VCHostingPersonal use` has 50 (100.0%) missing values	Missing
`VCHostingProfessional use` has 50 (100.0%) missing values	Missing
`OfficeStackAsyncHaveWorkedWith` has 24 (48.0%) missing values	Missing
`OfficeStackAsyncWantToWorkWith` has 32 (64.0%) missing values	Missing
`OfficeStackSyncHaveWorkedWith` has 11 (22.0%) missing values	Missing
`OfficeStackSyncWantToWorkWith` has 19 (38.0%) missing values	Missing
`Blockchain` has 3 (6.0%) missing values	Missing
`NEWSOSites` has 2 (4.0%) missing values	Missing
`SOVisitFreq` has 2 (4.0%) missing values	Missing
`SOAccount` has 2 (4.0%) missing values	Missing
`SOPartFreq` has 10 (20.0%) missing values	Missing
`SOComm` has 2 (4.0%) missing values	Missing
`Age` has 4 (8.0%) missing values	Missing
`Gender` has 4 (8.0%) missing values	Missing
`Trans` has 4 (8.0%) missing values	Missing
`Sexuality` has 6 (12.0%) missing values	Missing
`Ethnicity` has 6 (12.0%) missing values	Missing
`Accessibility` has 7 (14.0%) missing values	Missing
`MentalHealth` has 7 (14.0%) missing values	Missing
`TBranch` has 19 (38.0%) missing values	Missing
`ICorPM` has 33 (66.0%) missing values	Missing
`WorkExp` has 32 (64.0%) missing values	Missing
`Knowledge_1` has 32 (64.0%) missing values	Missing
`Knowledge_2` has 32 (64.0%) missing values	Missing
`Knowledge_3` has 32 (64.0%) missing values	Missing
`Knowledge_4` has 32 (64.0%) missing values	Missing
`Knowledge_5` has 32 (64.0%) missing values	Missing
`Knowledge_6` has 32 (64.0%) missing values	Missing
`Knowledge_7` has 32 (64.0%) missing values	Missing
`Frequency_1` has 32 (64.0%) missing values	Missing
`Frequency_2` has 32 (64.0%) missing values	Missing
`Frequency_3` has 32 (64.0%) missing values	Missing
`TimeSearching` has 32 (64.0%) missing values	Missing
`TimeAnswering` has 32 (64.0%) missing values	Missing
`Onboarding` has 32 (64.0%) missing values	Missing
`ProfessionalTech` has 33 (66.0%) missing values	Missing
`TrueFalse_1` has 33 (66.0%) missing values	Missing
`TrueFalse_2` has 32 (64.0%) missing values	Missing
`TrueFalse_3` has 32 (64.0%) missing values	Missing
`SurveyLength` has 3 (6.0%) missing values	Missing
`SurveyEase` has 2 (4.0%) missing values	Missing
`ConvertedCompYearly` has 26 (52.0%) missing values	Missing
`ResponseId` is uniformly distributed	Uniform
`LearnCodeOnline` is uniformly distributed	Uniform
`LanguageHaveWorkedWith` is uniformly distributed	Uniform
`LanguageWantToWorkWith` is uniformly distributed	Uniform
`WebframeHaveWorkedWith` is uniformly distributed	Uniform
`WebframeWantToWorkWith` is uniformly distributed	Uniform
`ResponseId` has unique values	Unique
`VCHostingPersonal use` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`VCHostingProfessional use` is an unsupported type, check if it needs cleaning or further analysis	Unsupported

Reproduction

Analysis started	2023-05-21 17:49:59.310993
Analysis finished	2023-05-21 17:51:11.955288
Duration	1 minute and 12.64 seconds
Software version	pandas-profiling v3.6.6
Download configuration	config.json

ResponseId
Real number (ℝ)

HIGH CORRELATION UNIFORM UNIQUE

Distinct	50
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	25.5

Minimum	1
Maximum	50
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	528.0 B

Quantile statistics

Minimum	1
5-th percentile	3.45
Q1	13.25
median	25.5
Q3	37.75
95-th percentile	47.55
Maximum	50
Range	49
Interquartile range (IQR)	24.5

Descriptive statistics

Standard deviation	14.57738
Coefficient of variation (CV)	0.57166195
Kurtosis	-1.2
Mean	25.5
Median Absolute Deviation (MAD)	12.5
Skewness	0
Sum	1275
Variance	212.5
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	1	2.0%
38	1	2.0%
28	1	2.0%
29	1	2.0%
30	1	2.0%
31	1	2.0%
32	1	2.0%
33	1	2.0%
34	1	2.0%
35	1	2.0%
Other values (40)	40	80.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	1	2.0%
2	1	2.0%
3	1	2.0%
4	1	2.0%
5	1	2.0%
6	1	2.0%
7	1	2.0%
8	1	2.0%
9	1	2.0%
10	1	2.0%

Value	Count	Frequency (%)
50	1	2.0%
49	1	2.0%
48	1	2.0%
47	1	2.0%
46	1	2.0%
45	1	2.0%
44	1	2.0%
43	1	2.0%
42	1	2.0%
41	1	2.0%

MainBranch
Categorical

Distinct	5
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	528.0 B

I am a developer by profession	36
I am not primarily a developer, but I write code sometimes as part of my work	6
I code primarily as a hobby	5
None of these	2
I am learning to code	1

Length

Max length	77
Median length	30
Mean length	34.48
Min length	13

Characters and Unicode

Total characters	1724
Distinct characters	26
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	2.0%

Sample

1st row	None of these
2nd row	I am a developer by profession
3rd row	I am not primarily a developer, but I write code sometimes as part of my work
4th row	I am a developer by profession
5th row	I am a developer by profession

Common Values

Value	Count	Frequency (%)
I am a developer by profession	36	72.0%
I am not primarily a developer, but I write code sometimes as part of my work	6	12.0%
I code primarily as a hobby	5	10.0%
None of these	2	4.0%
I am learning to code	1	2.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
i	54	15.3%
a	47	13.3%
am	43	12.2%
developer	42	11.9%
by	36	10.2%
profession	36	10.2%
code	12	3.4%
primarily	11	3.1%
as	11	3.1%
of	8	2.3%
Other values (12)	53	15.0%

Most occurring characters

Value	Count	Frequency (%)
	303	17.6%
e	199	11.5%
o	160	9.3%
a	119	6.9%
r	119	6.9%
s	97	5.6%
p	95	5.5%
m	72	4.2%
i	71	4.1%
y	58	3.4%
Other values (16)	431	25.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1359	78.8%
Space Separator	303	17.6%
Uppercase Letter	56	3.2%
Other Punctuation	6	0.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	199	14.6%
o	160	11.8%
a	119	8.8%
r	119	8.8%
s	97	7.1%
p	95	7.0%
m	72	5.3%
i	71	5.2%
y	58	4.3%
d	54	4.0%
Other values (12)	315	23.2%

Uppercase Letter

Value	Count	Frequency (%)
I	54	96.4%
N	2	3.6%

Space Separator

Value	Count	Frequency (%)
	303	100.0%

Other Punctuation

Value	Count	Frequency (%)
,	6	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1415	82.1%
Common	309	17.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	199	14.1%
o	160	11.3%
a	119	8.4%
r	119	8.4%
s	97	6.9%
p	95	6.7%
m	72	5.1%
i	71	5.0%
y	58	4.1%
I	54	3.8%
Other values (14)	371	26.2%

Common

Value	Count	Frequency (%)
	303	98.1%
,	6	1.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1724	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	303	17.6%
e	199	11.5%
o	160	9.3%
a	119	6.9%
r	119	6.9%
s	97	5.6%
p	95	5.5%
m	72	4.2%
i	71	4.1%
y	58	3.4%
Other values (16)	431	25.0%

Employment
Categorical

HIGH CORRELATION MISSING

Distinct	11
Distinct (%)	22.9%
Missing	2
Missing (%)	4.0%
Memory size	528.0 B

Employed, full-time	25
Student, full-time	6
Independent contractor, freelancer, or self-employed	5
Employed, full-time;Independent contractor, freelancer, or self-employed	3
Not employed, but looking for work	2
Other values (6)	7

Length

Max length	72
Median length	19
Mean length	28.208333
Min length	18

Characters and Unicode

Total characters	1354
Distinct characters	28
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5 ?
Unique (%)	10.4%

Sample

1st row	Employed, full-time
2nd row	Employed, full-time
3rd row	Employed, full-time
4th row	Employed, full-time
5th row	Student, full-time

Common Values

Value	Count	Frequency (%)
Employed, full-time	25	50.0%
Student, full-time	6	12.0%
Independent contractor, freelancer, or self-employed	5	10.0%
Employed, full-time;Independent contractor, freelancer, or self-employed	3	6.0%
Not employed, but looking for work	2	4.0%
Student, part-time;Employed, part-time	2	4.0%
Student, part-time	1	2.0%
Employed, part-time	1	2.0%
Not employed, and not looking for work	1	2.0%
Student, full-time;Employed, part-time	1	2.0%
(Missing)	2	4.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
employed	33	23.6%
full-time	31	22.1%
student	10	7.1%
contractor	8	5.7%
freelancer	8	5.7%
or	8	5.7%
self-employed	8	5.7%
part-time	6	4.3%
independent	5	3.6%
not	4	2.9%
Other values (9)	19	13.6%

Most occurring characters

Value	Count	Frequency (%)
e	166	12.3%
l	135	10.0%
t	104	7.7%
	92	6.8%
m	88	6.5%
o	84	6.2%
d	72	5.3%
,	63	4.7%
p	60	4.4%
n	56	4.1%
Other values (18)	434	32.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1085	80.1%
Space Separator	92	6.8%
Other Punctuation	70	5.2%
Uppercase Letter	55	4.1%
Dash Punctuation	52	3.8%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	166	15.3%
l	135	12.4%
t	104	9.6%
m	88	8.1%
o	84	7.7%
d	72	6.6%
p	60	5.5%
n	56	5.2%
f	55	5.1%
r	54	5.0%
Other values (10)	211	19.4%

Uppercase Letter

Value	Count	Frequency (%)
E	33	60.0%
S	11	20.0%
I	8	14.5%
N	3	5.5%

Other Punctuation

Value	Count	Frequency (%)
,	63	90.0%
;	7	10.0%

Space Separator

Value	Count	Frequency (%)
	92	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	52	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1140	84.2%
Common	214	15.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	166	14.6%
l	135	11.8%
t	104	9.1%
m	88	7.7%
o	84	7.4%
d	72	6.3%
p	60	5.3%
n	56	4.9%
f	55	4.8%
r	54	4.7%
Other values (14)	266	23.3%

Common

Value	Count	Frequency (%)
	92	43.0%
,	63	29.4%
-	52	24.3%
;	7	3.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1354	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	166	12.3%
l	135	10.0%
t	104	7.7%
	92	6.8%
m	88	6.5%
o	84	6.2%
d	72	5.3%
,	63	4.7%
p	60	4.4%
n	56	4.1%
Other values (18)	434	32.1%

RemoteWork
Categorical

HIGH CORRELATION MISSING

Distinct	3
Distinct (%)	7.9%
Missing	12
Missing (%)	24.0%
Memory size	528.0 B

Hybrid (some remote, some in-person)	18
Fully remote	17
Full in-person	3

Length

Max length	36
Median length	14
Mean length	23.526316
Min length	12

Characters and Unicode

Total characters	894
Distinct characters	21
Distinct categories	7 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Fully remote
2nd row	Hybrid (some remote, some in-person)
3rd row	Fully remote
4th row	Hybrid (some remote, some in-person)
5th row	Hybrid (some remote, some in-person)

Common Values

Value	Count	Frequency (%)
Hybrid (some remote, some in-person)	18	36.0%
Fully remote	17	34.0%
Full in-person	3	6.0%
(Missing)	12	24.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
some	36	27.7%
remote	35	26.9%
in-person	21	16.2%
hybrid	18	13.8%
fully	17	13.1%
full	3	2.3%

Most occurring characters

Value	Count	Frequency (%)
e	127	14.2%
o	92	10.3%
	92	10.3%
r	74	8.3%
m	71	7.9%
s	57	6.4%
n	42	4.7%
l	40	4.5%
i	39	4.4%
y	35	3.9%
Other values (11)	225	25.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	689	77.1%
Space Separator	92	10.3%
Uppercase Letter	38	4.3%
Dash Punctuation	21	2.3%
Open Punctuation	18	2.0%
Other Punctuation	18	2.0%
Close Punctuation	18	2.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	127	18.4%
o	92	13.4%
r	74	10.7%
m	71	10.3%
s	57	8.3%
n	42	6.1%
l	40	5.8%
i	39	5.7%
y	35	5.1%
t	35	5.1%
Other values (4)	77	11.2%

Uppercase Letter

Value	Count	Frequency (%)
F	20	52.6%
H	18	47.4%

Space Separator

Value	Count	Frequency (%)
	92	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	21	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	18	100.0%

Other Punctuation

Value	Count	Frequency (%)
,	18	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	18	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	727	81.3%
Common	167	18.7%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	127	17.5%
o	92	12.7%
r	74	10.2%
m	71	9.8%
s	57	7.8%
n	42	5.8%
l	40	5.5%
i	39	5.4%
y	35	4.8%
t	35	4.8%
Other values (6)	115	15.8%

Common

Value	Count	Frequency (%)
	92	55.1%
-	21	12.6%
(	18	10.8%
,	18	10.8%
)	18	10.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	894	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	127	14.2%
o	92	10.3%
	92	10.3%
r	74	8.3%
m	71	7.9%
s	57	6.4%
n	42	4.7%
l	40	4.5%
i	39	4.4%
y	35	3.9%
Other values (11)	225	25.2%

CodingActivities
Categorical

HIGH CORRELATION MISSING

Distinct	8
Distinct (%)	21.1%
Missing	12
Missing (%)	24.0%
Memory size	528.0 B

Hobby	14
I don’t code outside of work	11
Hobby;Contribute to open-source projects	6
Hobby;Contribute to open-source projects;Bootstrapping a business	2
Hobby;Freelance/contract work	2
Other values (3)	3

Length

Max length	65
Median length	64
Mean length	24.289474
Min length	5

Characters and Unicode

Total characters	923
Distinct characters	35
Distinct categories	8 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	7.9%

Sample

1st row	Hobby;Contribute to open-source projects
2nd row	Hobby
3rd row	I don’t code outside of work
4th row	Hobby
5th row	I don’t code outside of work

Common Values

Value	Count	Frequency (%)
Hobby	14	28.0%
I don’t code outside of work	11	22.0%
Hobby;Contribute to open-source projects	6	12.0%
Hobby;Contribute to open-source projects;Bootstrapping a business	2	4.0%
Hobby;Freelance/contract work	2	4.0%
Hobby;Contribute to open-source projects;Freelance/contract work	1	2.0%
Hobby;Bootstrapping a business	1	2.0%
Other (please specify):	1	2.0%
(Missing)	12	24.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
hobby	14	10.7%
work	14	10.7%
i	11	8.4%
don’t	11	8.4%
code	11	8.4%
outside	11	8.4%
of	11	8.4%
hobby;contribute	9	6.9%
to	9	6.9%
open-source	9	6.9%
Other values (10)	21	16.0%

Most occurring characters

Value	Count	Frequency (%)
o	138	15.0%
	93	10.1%
e	74	8.0%
t	71	7.7%
b	64	6.9%
r	51	5.5%
s	43	4.7%
n	41	4.4%
c	39	4.2%
d	33	3.6%
Other values (25)	276	29.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	736	79.7%
Space Separator	93	10.1%
Uppercase Letter	53	5.7%
Other Punctuation	19	2.1%
Final Punctuation	11	1.2%
Dash Punctuation	9	1.0%
Open Punctuation	1	0.1%
Close Punctuation	1	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	138	18.8%
e	74	10.1%
t	71	9.6%
b	64	8.7%
r	51	6.9%
s	43	5.8%
n	41	5.6%
c	39	5.3%
d	33	4.5%
u	32	4.3%
Other values (11)	150	20.4%

Uppercase Letter

Value	Count	Frequency (%)
H	26	49.1%
I	11	20.8%
C	9	17.0%
B	3	5.7%
F	3	5.7%
O	1	1.9%

Other Punctuation

Value	Count	Frequency (%)
;	15	78.9%
/	3	15.8%
:	1	5.3%

Space Separator

Value	Count	Frequency (%)
	93	100.0%

Final Punctuation

Value	Count	Frequency (%)
’	11	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	9	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	1	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	789	85.5%
Common	134	14.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	138	17.5%
e	74	9.4%
t	71	9.0%
b	64	8.1%
r	51	6.5%
s	43	5.4%
n	41	5.2%
c	39	4.9%
d	33	4.2%
u	32	4.1%
Other values (17)	203	25.7%

Common

Value	Count	Frequency (%)
	93	69.4%
;	15	11.2%
’	11	8.2%
-	9	6.7%
/	3	2.2%
(	1	0.7%
)	1	0.7%
:	1	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	912	98.8%
Punctuation	11	1.2%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	138	15.1%
	93	10.2%
e	74	8.1%
t	71	7.8%
b	64	7.0%
r	51	5.6%
s	43	4.7%
n	41	4.5%
c	39	4.3%
d	33	3.6%
Other values (24)	265	29.1%

Punctuation

Value	Count	Frequency (%)
’	11	100.0%

EdLevel
Categorical

HIGH CORRELATION MISSING

Distinct	8
Distinct (%)	17.0%
Missing	3
Missing (%)	6.0%
Memory size	528.0 B

Master’s degree (M.A., M.S., M.Eng., MBA, etc.)	13
Bachelor’s degree (B.A., B.S., B.Eng., etc.)	13
Secondary school (e.g. American high school, German Realschule or Gymnasium, etc.)	8
Some college/university study without earning a degree	8
Something else	2
Other values (3)	3

Length

Max length	82
Median length	54
Mean length	51.085106
Min length	14

Characters and Unicode

Total characters	2401
Distinct characters	35
Distinct categories	7 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	6.4%

Sample

1st row	Master’s degree (M.A., M.S., M.Eng., MBA, etc.)
2nd row	Bachelor’s degree (B.A., B.S., B.Eng., etc.)
3rd row	Bachelor’s degree (B.A., B.S., B.Eng., etc.)
4th row	Master’s degree (M.A., M.S., M.Eng., MBA, etc.)
5th row	Secondary school (e.g. American high school, German Realschule or Gymnasium, etc.)

Common Values

Value	Count	Frequency (%)
Master’s degree (M.A., M.S., M.Eng., MBA, etc.)	13	26.0%
Bachelor’s degree (B.A., B.S., B.Eng., etc.)	13	26.0%
Secondary school (e.g. American high school, German Realschule or Gymnasium, etc.)	8	16.0%
Some college/university study without earning a degree	8	16.0%
Something else	2	4.0%
Primary/elementary school	1	2.0%
Other doctoral degree (Ph.D., Ed.D., etc.)	1	2.0%
Associate degree (A.A., A.S., etc.)	1	2.0%
(Missing)	3	6.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
degree	36	10.9%
etc	36	10.9%
school	17	5.2%
b.eng	13	3.9%
b.a	13	3.9%
bachelor’s	13	3.9%
master’s	13	3.9%
mba	13	3.9%
m.eng	13	3.9%
m.s	13	3.9%
Other values (26)	150	45.5%

Most occurring characters

Value	Count	Frequency (%)
	283	11.8%
e	269	11.2%
.	216	9.0%
r	115	4.8%
,	111	4.6%
c	100	4.2%
g	96	4.0%
s	92	3.8%
o	92	3.8%
t	87	3.6%
Other values (25)	940	39.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1402	58.4%
Other Punctuation	336	14.0%
Space Separator	283	11.8%
Uppercase Letter	282	11.7%
Close Punctuation	36	1.5%
Open Punctuation	36	1.5%
Final Punctuation	26	1.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	269	19.2%
r	115	8.2%
c	100	7.1%
g	96	6.8%
s	92	6.6%
o	92	6.6%
t	87	6.2%
a	86	6.1%
n	85	6.1%
l	66	4.7%
Other values (8)	314	22.4%

Uppercase Letter

Value	Count	Frequency (%)
M	65	23.0%
B	65	23.0%
A	51	18.1%
S	45	16.0%
E	27	9.6%
G	16	5.7%
R	8	2.8%
P	2	0.7%
D	2	0.7%
O	1	0.4%

Other Punctuation

Value	Count	Frequency (%)
.	216	64.3%
,	111	33.0%
/	9	2.7%

Space Separator

Value	Count	Frequency (%)
	283	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	36	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	36	100.0%

Final Punctuation

Value	Count	Frequency (%)
’	26	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1684	70.1%
Common	717	29.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	269	16.0%
r	115	6.8%
c	100	5.9%
g	96	5.7%
s	92	5.5%
o	92	5.5%
t	87	5.2%
a	86	5.1%
n	85	5.0%
l	66	3.9%
Other values (18)	596	35.4%

Common

Value	Count	Frequency (%)
	283	39.5%
.	216	30.1%
,	111	15.5%
)	36	5.0%
(	36	5.0%
’	26	3.6%
/	9	1.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2375	98.9%
Punctuation	26	1.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	283	11.9%
e	269	11.3%
.	216	9.1%
r	115	4.8%
,	111	4.7%
c	100	4.2%
g	96	4.0%
s	92	3.9%
o	92	3.9%
t	87	3.7%
Other values (24)	914	38.5%

Punctuation

Value	Count	Frequency (%)
’	26	100.0%

LearnCode
Categorical

HIGH CORRELATION MISSING

Distinct	33
Distinct (%)	71.7%
Missing	4
Missing (%)	8.0%
Memory size	528.0 B

Books / Physical media;School (i.e., University, College, etc)	4
Other online resources (e.g., videos, blogs, forum);School (i.e., University, College, etc);On the job training	3
Other online resources (e.g., videos, blogs, forum)	3
Books / Physical media;Other online resources (e.g., videos, blogs, forum);School (i.e., University, College, etc)	3
Books / Physical media;Friend or family member;Other online resources (e.g., videos, blogs, forum);School (i.e., University, College, etc)	2
Other values (28)	31

Length

Max length	176
Median length	125.5
Mean length	92.5
Min length	22

Characters and Unicode

Total characters	4255
Distinct characters	37
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	25 ?
Unique (%)	54.3%

Sample

1st row	Books / Physical media;Friend or family member;Other online resources (e.g., videos, blogs, forum);School (i.e., University, College, etc)
2nd row	Books / Physical media;School (i.e., University, College, etc)
3rd row	Other online resources (e.g., videos, blogs, forum);School (i.e., University, College, etc);On the job training
4th row	Books / Physical media;School (i.e., University, College, etc)
5th row	Other online resources (e.g., videos, blogs, forum)

Common Values

Value	Count	Frequency (%)
Books / Physical media;School (i.e., University, College, etc)	4	8.0%
Other online resources (e.g., videos, blogs, forum);School (i.e., University, College, etc);On the job training	3	6.0%
Other online resources (e.g., videos, blogs, forum)	3	6.0%
Books / Physical media;Other online resources (e.g., videos, blogs, forum);School (i.e., University, College, etc)	3	6.0%
Books / Physical media;Friend or family member;Other online resources (e.g., videos, blogs, forum);School (i.e., University, College, etc)	2	4.0%
School (i.e., University, College, etc)	2	4.0%
Books / Physical media	2	4.0%
Other online resources (e.g., videos, blogs, forum);School (i.e., University, College, etc);Online Courses or Certification	2	4.0%
Books / Physical media;Other online resources (e.g., videos, blogs, forum);Online Courses or Certification	1	2.0%
Books / Physical media;Other online resources (e.g., videos, blogs, forum);School (i.e., University, College, etc);On the job training;Online Courses or Certification	1	2.0%
Other values (23)	23	46.0%
(Missing)	4	8.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
online	34	6.5%
e.g	33	6.3%
blogs	33	6.3%
videos	33	6.3%
resources	33	6.3%
i.e	26	5.0%
university	26	5.0%
college	26	5.0%
	23	4.4%
books	23	4.4%
Other values (36)	231	44.3%

Most occurring characters

Value	Count	Frequency (%)
	475	11.2%
e	450	10.6%
o	363	8.5%
i	287	6.7%
s	240	5.6%
r	233	5.5%
l	203	4.8%
,	177	4.2%
n	176	4.1%
t	142	3.3%
Other values (27)	1509	35.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	3020	71.0%
Space Separator	475	11.2%
Other Punctuation	402	9.4%
Uppercase Letter	232	5.5%
Close Punctuation	63	1.5%
Open Punctuation	63	1.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	450	14.9%
o	363	12.0%
i	287	9.5%
s	240	7.9%
r	233	7.7%
l	203	6.7%
n	176	5.8%
t	142	4.7%
c	129	4.3%
g	112	3.7%
Other values (12)	685	22.7%

Uppercase Letter

Value	Count	Frequency (%)
C	63	27.2%
O	62	26.7%
B	26	11.2%
U	26	11.2%
S	26	11.2%
P	23	9.9%
F	6	2.6%

Other Punctuation

Value	Count	Frequency (%)
,	177	44.0%
.	118	29.4%
;	80	19.9%
/	23	5.7%
:	4	1.0%

Space Separator

Value	Count	Frequency (%)
	475	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	63	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	63	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	3252	76.4%
Common	1003	23.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	450	13.8%
o	363	11.2%
i	287	8.8%
s	240	7.4%
r	233	7.2%
l	203	6.2%
n	176	5.4%
t	142	4.4%
c	129	4.0%
g	112	3.4%
Other values (19)	917	28.2%

Common

Value	Count	Frequency (%)
	475	47.4%
,	177	17.6%
.	118	11.8%
;	80	8.0%
)	63	6.3%
(	63	6.3%
/	23	2.3%
:	4	0.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4255	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	475	11.2%
e	450	10.6%
o	363	8.5%
i	287	6.7%
s	240	5.6%
r	233	5.5%
l	203	4.8%
,	177	4.2%
n	176	4.1%
t	142	3.3%
Other values (27)	1509	35.5%

LearnCodeOnline
Categorical

HIGH CORRELATION MISSING UNIFORM

Distinct	32
Distinct (%)	97.0%
Missing	17
Missing (%)	34.0%
Memory size	528.0 B

Technical documentation;Blogs;Stack Overflow	2
Technical documentation;Blogs;Written Tutorials;Stack Overflow;Online books;Video-based Online Courses;Online forum;How-to videos;Written-based Online Courses	1
Technical documentation;Blogs	1
Technical documentation;Blogs;Stack Overflow;Online forum	1
Technical documentation;Blogs;Written Tutorials;Stack Overflow;Video-based Online Courses	1
Other values (27)	27

Length

Max length	239
Median length	108
Mean length	102.36364
Min length	29

Characters and Unicode

Total characters	3378
Distinct characters	42
Distinct categories	7 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	31 ?
Unique (%)	93.9%

Sample

1st row	Technical documentation;Blogs;Programming Games;Written Tutorials;Stack Overflow
2nd row	Technical documentation;Blogs;Stack Overflow;Online books;Video-based Online Courses;Online challenges (e.g., daily or weekly coding challenges)
3rd row	Stack Overflow;Video-based Online Courses
4th row	Technical documentation;Blogs;Written Tutorials;Stack Overflow;Online books;Online forum
5th row	Technical documentation;Blogs;Written Tutorials;Stack Overflow;Video-based Online Courses;How-to videos;Written-based Online Courses

Common Values

Value	Count	Frequency (%)
Technical documentation;Blogs;Stack Overflow	2	4.0%
Technical documentation;Blogs;Written Tutorials;Stack Overflow;Online books;Video-based Online Courses;Online forum;How-to videos;Written-based Online Courses	1	2.0%
Technical documentation;Blogs	1	2.0%
Technical documentation;Blogs;Stack Overflow;Online forum	1	2.0%
Technical documentation;Blogs;Written Tutorials;Stack Overflow;Video-based Online Courses	1	2.0%
Technical documentation;Blogs;Written Tutorials;Stack Overflow;Video-based Online Courses;How-to videos;Auditory material (e.g., podcasts);Coding sessions (live or recorded)	1	2.0%
Blogs;Written Tutorials;Stack Overflow;Video-based Online Courses;Online challenges (e.g., daily or weekly coding challenges);Online forum;How-to videos;Interactive tutorial	1	2.0%
Technical documentation;Blogs;Written Tutorials;Stack Overflow;Online forum;How-to videos	1	2.0%
Technical documentation;Online challenges (e.g., daily or weekly coding challenges);How-to videos	1	2.0%
Technical documentation;Blogs;Written Tutorials;Stack Overflow;Video-based Online Courses;Written-based Online Courses	1	2.0%
Other values (22)	22	44.0%
(Missing)	17	34.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
technical	29	11.3%
online	25	9.8%
tutorials;stack	19	7.4%
documentation;blogs;written	13	5.1%
overflow;online	10	3.9%
overflow;video-based	10	3.9%
or	9	3.5%
videos;written-based	7	2.7%
courses	7	2.7%
courses;how-to	7	2.7%
Other values (48)	120	46.9%

Most occurring characters

Value	Count	Frequency (%)
e	311	9.2%
o	286	8.5%
n	234	6.9%
i	225	6.7%
	223	6.6%
t	209	6.2%
l	184	5.4%
s	179	5.3%
a	162	4.8%
r	148	4.4%
Other values (32)	1217	36.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	2644	78.3%
Uppercase Letter	279	8.3%
Space Separator	223	6.6%
Other Punctuation	165	4.9%
Dash Punctuation	43	1.3%
Open Punctuation	12	0.4%
Close Punctuation	12	0.4%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	311	11.8%
o	286	10.8%
n	234	8.9%
i	225	8.5%
t	209	7.9%
l	184	7.0%
s	179	6.8%
a	162	6.1%
r	148	5.6%
c	140	5.3%
Other values (12)	566	21.4%

Uppercase Letter

Value	Count	Frequency (%)
O	74	26.5%
T	49	17.6%
C	30	10.8%
W	29	10.4%
S	28	10.0%
B	25	9.0%
H	18	6.5%
V	16	5.7%
I	5	1.8%
A	2	0.7%
Other values (2)	3	1.1%

Other Punctuation

Value	Count	Frequency (%)
;	146	88.5%
.	12	7.3%
,	6	3.6%
:	1	0.6%

Space Separator

Value	Count	Frequency (%)
	223	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	43	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	12	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	12	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	2923	86.5%
Common	455	13.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	311	10.6%
o	286	9.8%
n	234	8.0%
i	225	7.7%
t	209	7.2%
l	184	6.3%
s	179	6.1%
a	162	5.5%
r	148	5.1%
c	140	4.8%
Other values (24)	845	28.9%

Common

Value	Count	Frequency (%)
	223	49.0%
;	146	32.1%
-	43	9.5%
(	12	2.6%
.	12	2.6%
)	12	2.6%
,	6	1.3%
:	1	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3378	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	311	9.2%
o	286	8.5%
n	234	6.9%
i	225	6.7%
	223	6.6%
t	209	6.2%
l	184	5.4%
s	179	5.3%
a	162	4.8%
r	148	4.4%
Other values (32)	1217	36.0%

LearnCodeCoursesCert
Categorical

HIGH CORRELATION MISSING

Distinct	9
Distinct (%)	81.8%
Missing	39
Missing (%)	78.0%
Memory size	528.0 B

Udemy;Codecademy	2
Udemy	2
Coursera;Udemy	1
Coursera;Pluralsight	1
Coursera;Udemy;Codecademy;edX;Udacity	1
Other values (4)	4

Length

Max length	37
Median length	22
Mean length	17
Min length	5

Characters and Unicode

Total characters	187
Distinct characters	21
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	7 ?
Unique (%)	63.6%

Sample

1st row	Coursera;Udemy
2nd row	Udemy;Codecademy
3rd row	Coursera;Pluralsight
4th row	Coursera;Udemy;Codecademy;edX;Udacity
5th row	Coursera;Udemy;Pluralsight;edX

Common Values

Value	Count	Frequency (%)
Udemy;Codecademy	2	4.0%
Udemy	2	4.0%
Coursera;Udemy	1	2.0%
Coursera;Pluralsight	1	2.0%
Coursera;Udemy;Codecademy;edX;Udacity	1	2.0%
Coursera;Udemy;Pluralsight;edX	1	2.0%
Other	1	2.0%
Coursera;Udemy;Udacity	1	2.0%
Udemy;Pluralsight	1	2.0%
(Missing)	39	78.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
udemy;codecademy	2	18.2%
udemy	2	18.2%
coursera;udemy	1	9.1%
coursera;pluralsight	1	9.1%
coursera;udemy;codecademy;edx;udacity	1	9.1%
coursera;udemy;pluralsight;edx	1	9.1%
other	1	9.1%
coursera;udemy;udacity	1	9.1%
udemy;pluralsight	1	9.1%

Most occurring characters

Value	Count	Frequency (%)
e	23	12.3%
d	19	10.2%
y	14	7.5%
;	14	7.5%
r	14	7.5%
a	13	7.0%
m	12	6.4%
U	11	5.9%
s	8	4.3%
u	8	4.3%
Other values (11)	51	27.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	148	79.1%
Uppercase Letter	25	13.4%
Other Punctuation	14	7.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	23	15.5%
d	19	12.8%
y	14	9.5%
r	14	9.5%
a	13	8.8%
m	12	8.1%
s	8	5.4%
u	8	5.4%
o	8	5.4%
l	6	4.1%
Other values (5)	23	15.5%

Uppercase Letter

Value	Count	Frequency (%)
U	11	44.0%
C	8	32.0%
P	3	12.0%
X	2	8.0%
O	1	4.0%

Other Punctuation

Value	Count	Frequency (%)
;	14	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	173	92.5%
Common	14	7.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	23	13.3%
d	19	11.0%
y	14	8.1%
r	14	8.1%
a	13	7.5%
m	12	6.9%
U	11	6.4%
s	8	4.6%
u	8	4.6%
o	8	4.6%
Other values (10)	43	24.9%

Common

Value	Count	Frequency (%)
;	14	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	187	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	23	12.3%
d	19	10.2%
y	14	7.5%
;	14	7.5%
r	14	7.5%
a	13	7.0%
m	12	6.4%
U	11	5.9%
s	8	4.3%
u	8	4.3%
Other values (11)	51	27.3%

YearsCode
Real number (ℝ)

HIGH CORRELATION MISSING

Distinct	24
Distinct (%)	51.1%
Missing	3
Missing (%)	6.0%
Infinite	0
Infinite (%)	0.0%
Mean	13.021277

Minimum	1
Maximum	40
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	528.0 B

Quantile statistics

Minimum	1
5-th percentile	2
Q1	5
median	10
Q3	19.5
95-th percentile	36.7
Maximum	40
Range	39
Interquartile range (IQR)	14.5

Descriptive statistics

Standard deviation	10.526342
Coefficient of variation (CV)	0.80839558
Kurtosis	0.67409307
Mean	13.021277
Median Absolute Deviation (MAD)	6
Skewness	1.1449929
Sum	612
Variance	110.80389
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=24)

Value	Count	Frequency (%)
6	4	8.0%
4	4	8.0%
12	3	6.0%
20	3	6.0%
3	3	6.0%
7	3	6.0%
10	2	4.0%
40	2	4.0%
16	2	4.0%
5	2	4.0%
Other values (14)	19	38.0%
(Missing)	3	6.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	2	4.0%
2	2	4.0%
3	3	6.0%
4	4	8.0%
5	2	4.0%
6	4	8.0%
7	3	6.0%
8	2	4.0%
10	2	4.0%
11	1	2.0%

Value	Count	Frequency (%)
40	2	4.0%
37	1	2.0%
36	1	2.0%
27	1	2.0%
25	1	2.0%
24	2	4.0%
22	1	2.0%
20	3	6.0%
19	1	2.0%
16	2	4.0%

YearsCodePro
Real number (ℝ)

HIGH CORRELATION MISSING

Distinct	18
Distinct (%)	54.5%
Missing	17
Missing (%)	34.0%
Infinite	0
Infinite (%)	0.0%
Mean	11.454545

Minimum	2
Maximum	40
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	528.0 B

Quantile statistics

Minimum	2
5-th percentile	3
Q1	5
median	7
Q3	17
95-th percentile	27
Maximum	40
Range	38
Interquartile range (IQR)	12

Descriptive statistics

Standard deviation	9.196096
Coefficient of variation (CV)	0.80283378
Kurtosis	1.4716573
Mean	11.454545
Median Absolute Deviation (MAD)	4
Skewness	1.2906832
Sum	378
Variance	84.568182
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=18)

Value	Count	Frequency (%)
5	6	12.0%
4	4	8.0%
3	3	6.0%
6	2	4.0%
10	2	4.0%
15	2	4.0%
22	2	4.0%
14	2	4.0%
30	1	2.0%
2	1	2.0%
Other values (8)	8	16.0%
(Missing)	17	34.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
2	1	2.0%
3	3	6.0%
4	4	8.0%
5	6	12.0%
6	2	4.0%
7	1	2.0%
9	1	2.0%
10	2	4.0%
14	2	4.0%
15	2	4.0%

Value	Count	Frequency (%)
40	1	2.0%
30	1	2.0%
25	1	2.0%
22	2	4.0%
21	1	2.0%
20	1	2.0%
18	1	2.0%
17	1	2.0%
15	2	4.0%
14	2	4.0%

DevType
Categorical

HIGH CORRELATION MISSING

Distinct	24
Distinct (%)	63.2%
Missing	12
Missing (%)	24.0%
Memory size	528.0 B

Developer, full-stack	8
Developer, full-stack;Developer, back-end	3
Developer, back-end	3
Student	2
Developer, front-end;Developer, full-stack;Developer, back-end;Database administrator	2
Other values (19)	20

Length

Max length	294
Median length	109
Mean length	53.5
Min length	7

Characters and Unicode

Total characters	2033
Distinct characters	37
Distinct categories	7 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	18 ?
Unique (%)	47.4%

Sample

1st row	Data scientist or machine learning specialist;Developer, front-end;Engineer, data;Engineer, site reliability
2nd row	Developer, full-stack
3rd row	Developer, front-end;Developer, full-stack;Developer, back-end;Developer, desktop or enterprise applications;Developer, QA or test
4th row	Developer, full-stack;Student
5th row	Developer, back-end

Common Values

Value	Count	Frequency (%)
Developer, full-stack	8	16.0%
Developer, full-stack;Developer, back-end	3	6.0%
Developer, back-end	3	6.0%
Student	2	4.0%
Developer, front-end;Developer, full-stack;Developer, back-end;Database administrator	2	4.0%
Developer, back-end;Developer, desktop or enterprise applications	2	4.0%
Developer, desktop or enterprise applications;Developer, mobile;Educator	1	2.0%
Engineering manager	1	2.0%
Developer, front-end	1	2.0%
Data scientist or machine learning specialist;Engineer, data;Developer, back-end	1	2.0%
Other values (14)	14	28.0%
(Missing)	12	24.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
developer	30	17.8%
or	15	8.9%
full-stack;developer	9	5.3%
full-stack	8	4.7%
back-end	7	4.1%
desktop	6	3.6%
enterprise	6	3.6%
back-end;developer	5	3.0%
front-end;developer	5	3.0%
applications	4	2.4%
Other values (50)	74	43.8%

Most occurring characters

Value	Count	Frequency (%)
e	313	15.4%
r	138	6.8%
	131	6.4%
l	123	6.1%
a	120	5.9%
o	108	5.3%
t	101	5.0%
p	98	4.8%
n	97	4.8%
s	86	4.2%
Other values (27)	718	35.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1641	80.7%
Space Separator	131	6.4%
Other Punctuation	117	5.8%
Uppercase Letter	97	4.8%
Dash Punctuation	45	2.2%
Open Punctuation	1	< 0.1%
Close Punctuation	1	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	313	19.1%
r	138	8.4%
l	123	7.5%
a	120	7.3%
o	108	6.6%
t	101	6.2%
p	98	6.0%
n	97	5.9%
s	86	5.2%
i	79	4.8%
Other values (12)	378	23.0%

Uppercase Letter

Value	Count	Frequency (%)
D	71	73.2%
E	8	8.2%
S	4	4.1%
A	4	4.1%
O	4	4.1%
C	3	3.1%
Q	2	2.1%
P	1	1.0%

Other Punctuation

Value	Count	Frequency (%)
,	64	54.7%
;	52	44.4%
:	1	0.9%

Space Separator

Value	Count	Frequency (%)
	131	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	45	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	1	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1738	85.5%
Common	295	14.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	313	18.0%
r	138	7.9%
l	123	7.1%
a	120	6.9%
o	108	6.2%
t	101	5.8%
p	98	5.6%
n	97	5.6%
s	86	4.9%
i	79	4.5%
Other values (20)	475	27.3%

Common

Value	Count	Frequency (%)
	131	44.4%
,	64	21.7%
;	52	17.6%
-	45	15.3%
(	1	0.3%
)	1	0.3%
:	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2033	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	313	15.4%
r	138	6.8%
	131	6.4%
l	123	6.1%
a	120	5.9%
o	108	5.3%
t	101	5.0%
p	98	4.8%
n	97	4.8%
s	86	4.2%
Other values (27)	718	35.3%

OrgSize
Categorical

HIGH CORRELATION MISSING

Distinct	9
Distinct (%)	27.3%
Missing	17
Missing (%)	34.0%
Memory size	528.0 B

20 to 99 employees	11
100 to 499 employees	7
Just me - I am a freelancer, sole proprietor, etc.	5
2 to 9 employees	3
1,000 to 4,999 employees	2
Other values (4)	5

Length

Max length	50
Median length	24
Mean length	23.878788
Min length	12

Characters and Unicode

Total characters	788
Distinct characters	31
Distinct categories	7 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	9.1%

Sample

1st row	20 to 99 employees
2nd row	100 to 499 employees
3rd row	20 to 99 employees
4th row	I don’t know
5th row	Just me - I am a freelancer, sole proprietor, etc.

Common Values

Value	Count	Frequency (%)
20 to 99 employees	11	22.0%
100 to 499 employees	7	14.0%
Just me - I am a freelancer, sole proprietor, etc.	5	10.0%
2 to 9 employees	3	6.0%
1,000 to 4,999 employees	2	4.0%
10,000 or more employees	2	4.0%
I don’t know	1	2.0%
5,000 to 9,999 employees	1	2.0%
500 to 999 employees	1	2.0%
(Missing)	17	34.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
employees	27	16.8%
to	25	15.5%
20	11	6.8%
99	11	6.8%
100	7	4.3%
499	7	4.3%
i	6	3.7%
a	5	3.1%
etc	5	3.1%
sole	5	3.1%
Other values (19)	52	32.3%

Most occurring characters

Value	Count	Frequency (%)
	128	16.2%
e	118	15.0%
o	73	9.3%
9	52	6.6%
0	44	5.6%
t	41	5.2%
m	39	4.9%
s	37	4.7%
p	37	4.7%
l	37	4.7%
Other values (21)	182	23.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	488	61.9%
Decimal Number	132	16.8%
Space Separator	128	16.2%
Other Punctuation	23	2.9%
Uppercase Letter	11	1.4%
Dash Punctuation	5	0.6%
Final Punctuation	1	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	118	24.2%
o	73	15.0%
t	41	8.4%
m	39	8.0%
s	37	7.6%
p	37	7.6%
l	37	7.6%
r	29	5.9%
y	27	5.5%
a	15	3.1%
Other values (8)	35	7.2%

Decimal Number

Value	Count	Frequency (%)
9	52	39.4%
0	44	33.3%
2	14	10.6%
1	11	8.3%
4	9	6.8%
5	2	1.5%

Other Punctuation

Value	Count	Frequency (%)
,	18	78.3%
.	5	21.7%

Uppercase Letter

Value	Count	Frequency (%)
I	6	54.5%
J	5	45.5%

Space Separator

Value	Count	Frequency (%)
	128	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	5	100.0%

Final Punctuation

Value	Count	Frequency (%)
’	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	499	63.3%
Common	289	36.7%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	118	23.6%
o	73	14.6%
t	41	8.2%
m	39	7.8%
s	37	7.4%
p	37	7.4%
l	37	7.4%
r	29	5.8%
y	27	5.4%
a	15	3.0%
Other values (10)	46	9.2%

Common

Value	Count	Frequency (%)
	128	44.3%
9	52	18.0%
0	44	15.2%
,	18	6.2%
2	14	4.8%
1	11	3.8%
4	9	3.1%
.	5	1.7%
-	5	1.7%
5	2	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	787	99.9%
Punctuation	1	0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	128	16.3%
e	118	15.0%
o	73	9.3%
9	52	6.6%
0	44	5.6%
t	41	5.2%
m	39	5.0%
s	37	4.7%
p	37	4.7%
l	37	4.7%
Other values (20)	181	23.0%

Punctuation

Value	Count	Frequency (%)
’	1	100.0%

PurchaseInfluence
Categorical

HIGH CORRELATION MISSING

Distinct	3
Distinct (%)	9.1%
Missing	17
Missing (%)	34.0%
Memory size	528.0 B

I have some influence	16
I have little or no influence	9
I have a great deal of influence	8

Length

Max length	32
Median length	29
Mean length	25.848485
Min length	21

Characters and Unicode

Total characters	853
Distinct characters	19
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	I have some influence
2nd row	I have some influence
3rd row	I have some influence
4th row	I have little or no influence
5th row	I have a great deal of influence

Common Values

Value	Count	Frequency (%)
I have some influence	16	32.0%
I have little or no influence	9	18.0%
I have a great deal of influence	8	16.0%
(Missing)	17	34.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
i	33	19.0%
have	33	19.0%
influence	33	19.0%
some	16	9.2%
little	9	5.2%
or	9	5.2%
no	9	5.2%
a	8	4.6%
great	8	4.6%
deal	8	4.6%

Most occurring characters

Value	Count	Frequency (%)
	141	16.5%
e	140	16.4%
n	75	8.8%
l	59	6.9%
a	57	6.7%
i	42	4.9%
o	42	4.9%
f	41	4.8%
c	33	3.9%
u	33	3.9%
Other values (9)	190	22.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	679	79.6%
Space Separator	141	16.5%
Uppercase Letter	33	3.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	140	20.6%
n	75	11.0%
l	59	8.7%
a	57	8.4%
i	42	6.2%
o	42	6.2%
f	41	6.0%
c	33	4.9%
u	33	4.9%
v	33	4.9%
Other values (7)	124	18.3%

Space Separator

Value	Count	Frequency (%)
	141	100.0%

Uppercase Letter

Value	Count	Frequency (%)
I	33	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	712	83.5%
Common	141	16.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	140	19.7%
n	75	10.5%
l	59	8.3%
a	57	8.0%
i	42	5.9%
o	42	5.9%
f	41	5.8%
c	33	4.6%
u	33	4.6%
I	33	4.6%
Other values (8)	157	22.1%

Common

Value	Count	Frequency (%)
	141	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	853	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	141	16.5%
e	140	16.4%
n	75	8.8%
l	59	6.9%
a	57	6.7%
i	42	4.9%
o	42	4.9%
f	41	4.8%
c	33	3.9%
u	33	3.9%
Other values (9)	190	22.3%

BuyNewTool
Categorical

HIGH CORRELATION MISSING

Distinct	19
Distinct (%)	42.2%
Missing	5
Missing (%)	10.0%
Memory size	528.0 B

Start a free trial;Visit developer communities like Stack Overflow;Ask developers I know/work with	10
Start a free trial	6
Start a free trial;Ask developers I know/work with	5
Start a free trial;Visit developer communities like Stack Overflow	4
Other (please specify):	4
Other values (14)	16

Length

Max length	213
Median length	124
Mean length	72.288889
Min length	18

Characters and Unicode

Total characters	3253
Distinct characters	36
Distinct categories	7 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	12 ?
Unique (%)	26.7%

Sample

1st row	Other (please specify):
2nd row	Start a free trial;Visit developer communities like Stack Overflow
3rd row	Other (please specify):
4th row	Start a free trial;Visit developer communities like Stack Overflow
5th row	Start a free trial

Common Values

Value	Count	Frequency (%)
Start a free trial;Visit developer communities like Stack Overflow;Ask developers I know/work with	10	20.0%
Start a free trial	6	12.0%
Start a free trial;Ask developers I know/work with	5	10.0%
Start a free trial;Visit developer communities like Stack Overflow	4	8.0%
Other (please specify):	4	8.0%
Visit developer communities like Stack Overflow	2	4.0%
Visit developer communities like Stack Overflow;Read ratings or reviews on third party sites like G2Crowd	2	4.0%
Other (please specify):;Ask developers I know/work with	1	2.0%
Visit developer communities like Stack Overflow;Ask developers I know/work with;Read ratings or reviews on third party sites like G2Crowd	1	2.0%
Start a free trial;Visit developer communities like Stack Overflow;Ask developers I know/work with;Research companies that have advertised on sites I visit;Read ratings or reviews on third party sites like G2Crowd	1	2.0%
Other values (9)	9	18.0%
(Missing)	5	10.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
a	32	6.9%
free	32	6.9%
like	31	6.7%
start	31	6.7%
i	27	5.8%
stack	24	5.2%
communities	24	5.2%
developer	24	5.2%
developers	23	5.0%
know/work	23	5.0%
Other values (31)	191	41.3%

Most occurring characters

Value	Count	Frequency (%)
	417	12.8%
e	368	11.3%
r	247	7.6%
t	246	7.6%
i	237	7.3%
o	170	5.2%
a	168	5.2%
s	160	4.9%
l	141	4.3%
k	124	3.8%
Other values (26)	975	30.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	2547	78.3%
Space Separator	417	12.8%
Uppercase Letter	186	5.7%
Other Punctuation	82	2.5%
Open Punctuation	7	0.2%
Close Punctuation	7	0.2%
Decimal Number	7	0.2%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	368	14.4%
r	247	9.7%
t	246	9.7%
i	237	9.3%
o	170	6.7%
a	168	6.6%
s	160	6.3%
l	141	5.5%
k	124	4.9%
w	107	4.2%
Other values (11)	579	22.7%

Uppercase Letter

Value	Count	Frequency (%)
S	56	30.1%
O	31	16.7%
I	27	14.5%
V	24	12.9%
A	23	12.4%
R	11	5.9%
G	7	3.8%
C	7	3.8%

Other Punctuation

Value	Count	Frequency (%)
;	52	63.4%
/	23	28.0%
:	7	8.5%

Space Separator

Value	Count	Frequency (%)
	417	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	7	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	7	100.0%

Decimal Number

Value	Count	Frequency (%)
2	7	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	2733	84.0%
Common	520	16.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	368	13.5%
r	247	9.0%
t	246	9.0%
i	237	8.7%
o	170	6.2%
a	168	6.1%
s	160	5.9%
l	141	5.2%
k	124	4.5%
w	107	3.9%
Other values (19)	765	28.0%

Common

Value	Count	Frequency (%)
	417	80.2%
;	52	10.0%
/	23	4.4%
(	7	1.3%
)	7	1.3%
:	7	1.3%
2	7	1.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3253	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	417	12.8%
e	368	11.3%
r	247	7.6%
t	246	7.6%
i	237	7.3%
o	170	5.2%
a	168	5.2%
s	160	4.9%
l	141	4.3%
k	124	3.8%
Other values (26)	975	30.0%

Country
Categorical

HIGH CORRELATION MISSING

Distinct	21
Distinct (%)	43.8%
Missing	2
Missing (%)	4.0%
Memory size	528.0 B

United States of America	9
Israel	7
Austria	4
Germany	4
Canada	4
Other values (16)	20

Length

Max length	52
Median length	24
Mean length	12.375
Min length	4

Characters and Unicode

Total characters	594
Distinct characters	37
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	12 ?
Unique (%)	25.0%

Sample

1st row	Canada
2nd row	United Kingdom of Great Britain and Northern Ireland
3rd row	Israel
4th row	United States of America
5th row	Germany

Common Values

Value	Count	Frequency (%)
United States of America	9	18.0%
Israel	7	14.0%
Austria	4	8.0%
Germany	4	8.0%
Canada	4	8.0%
Netherlands	2	4.0%
Czech Republic	2	4.0%
India	2	4.0%
United Kingdom of Great Britain and Northern Ireland	2	4.0%
Croatia	1	2.0%
Other values (11)	11	22.0%
(Missing)	2	4.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
united	11	12.0%
of	11	12.0%
america	9	9.8%
states	9	9.8%
israel	7	7.6%
austria	4	4.3%
germany	4	4.3%
canada	4	4.3%
ireland	3	3.3%
great	2	2.2%
Other values (20)	28	30.4%

Most occurring characters

Value	Count	Frequency (%)
a	74	12.5%
e	61	10.3%
t	45	7.6%
	44	7.4%
r	44	7.4%
i	40	6.7%
n	39	6.6%
d	30	5.1%
s	26	4.4%
o	20	3.4%
Other values (27)	171	28.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	471	79.3%
Uppercase Letter	79	13.3%
Space Separator	44	7.4%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	74	15.7%
e	61	13.0%
t	45	9.6%
r	44	9.3%
i	40	8.5%
n	39	8.3%
d	30	6.4%
s	26	5.5%
o	20	4.2%
l	18	3.8%
Other values (13)	74	15.7%

Uppercase Letter

Value	Count	Frequency (%)
A	14	17.7%
I	14	17.7%
S	12	15.2%
U	11	13.9%
C	7	8.9%
G	6	7.6%
N	5	6.3%
R	3	3.8%
B	2	2.5%
K	2	2.5%
Other values (3)	3	3.8%

Space Separator

Value	Count	Frequency (%)
	44	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	550	92.6%
Common	44	7.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	74	13.5%
e	61	11.1%
t	45	8.2%
r	44	8.0%
i	40	7.3%
n	39	7.1%
d	30	5.5%
s	26	4.7%
o	20	3.6%
l	18	3.3%
Other values (26)	153	27.8%

Common

Value	Count	Frequency (%)
	44	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	594	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	74	12.5%
e	61	10.3%
t	45	7.6%
	44	7.4%
r	44	7.4%
i	40	6.7%
n	39	6.6%
d	30	5.1%
s	26	4.4%
o	20	3.4%
Other values (27)	171	28.8%

Currency
Categorical

HIGH CORRELATION MISSING

Distinct	10
Distinct (%)	29.4%
Missing	16
Missing (%)	32.0%
Memory size	528.0 B

EUR European Euro	10
USD United States dollar	9
ILS Israeli new shekel	4
CAD Canadian dollar	3
GBP Pound sterling	2
Other values (5)	6

Length

Max length	24
Median length	22
Mean length	19.705882
Min length	16

Characters and Unicode

Total characters	670
Distinct characters	38
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4 ?
Unique (%)	11.8%

Sample

1st row	CAD Canadian dollar
2nd row	GBP Pound sterling
3rd row	ILS Israeli new shekel
4th row	USD United States dollar
5th row	EUR European Euro

Common Values

Value	Count	Frequency (%)
EUR European Euro	10	20.0%
USD United States dollar	9	18.0%
ILS Israeli new shekel	4	8.0%
CAD Canadian dollar	3	6.0%
GBP Pound sterling	2	4.0%
CZK Czech koruna	2	4.0%
HRK Croatian kuna	1	2.0%
AUD Australian dollar	1	2.0%
RUB Russian ruble	1	2.0%
PLN Polish zloty	1	2.0%
(Missing)	16	32.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
dollar	13	11.3%
eur	10	8.7%
euro	10	8.7%
european	10	8.7%
usd	9	7.8%
united	9	7.8%
states	9	7.8%
ils	4	3.5%
israeli	4	3.5%
new	4	3.5%
Other values (20)	33	28.7%

Most occurring characters

Value	Count	Frequency (%)
	57	8.5%
a	53	7.9%
e	49	7.3%
r	44	6.6%
l	40	6.0%
o	40	6.0%
n	39	5.8%
t	32	4.8%
E	30	4.5%
U	30	4.5%
Other values (28)	256	38.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	434	64.8%
Uppercase Letter	155	23.1%
Space Separator	57	8.5%
Control	24	3.6%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	53	12.2%
e	49	11.3%
r	44	10.1%
l	40	9.2%
o	40	9.2%
n	39	9.0%
t	32	7.4%
u	28	6.5%
d	27	6.2%
s	23	5.3%
Other values (10)	59	13.6%

Uppercase Letter

Value	Count	Frequency (%)
E	30	19.4%
U	30	19.4%
S	22	14.2%
D	13	8.4%
R	13	8.4%
C	11	7.1%
I	8	5.2%
P	6	3.9%
L	5	3.2%
A	5	3.2%
Other values (6)	12	7.7%

Space Separator

Value	Count	Frequency (%)
	57	100.0%

Control

Value	Count	Frequency (%)
	24	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	589	87.9%
Common	81	12.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	53	9.0%
e	49	8.3%
r	44	7.5%
l	40	6.8%
o	40	6.8%
n	39	6.6%
t	32	5.4%
E	30	5.1%
U	30	5.1%
u	28	4.8%
Other values (26)	204	34.6%

Common

Value	Count	Frequency (%)
	57	70.4%
	24	29.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	670	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	57	8.5%
a	53	7.9%
e	49	7.3%
r	44	6.6%
l	40	6.0%
o	40	6.0%
n	39	5.8%
t	32	4.8%
E	30	4.5%
U	30	4.5%
Other values (28)	256	38.2%

CompTotal
Real number (ℝ)

HIGH CORRELATION MISSING

Distinct	20
Distinct (%)	83.3%
Missing	26
Missing (%)	52.0%
Infinite	0
Infinite (%)	0.0%
Mean	79823.333

Minimum	400
Maximum	194400
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	528.0 B

Quantile statistics

Minimum	400
5-th percentile	4000
Q1	32000
median	75000
Q3	126250
95-th percentile	181750
Maximum	194400
Range	194000
Interquartile range (IQR)	94250

Descriptive statistics

Standard deviation	56585.3
Coefficient of variation (CV)	0.7088817
Kurtosis	-0.70310023
Mean	79823.333
Median Absolute Deviation (MAD)	44000
Skewness	0.37871952
Sum	1915760
Variance	3.2018962 × 10⁹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=20)

Value	Count	Frequency (%)
130000	3	6.0%
32000	2	4.0%
4000	2	4.0%
48000	1	2.0%
106960	1	2.0%
135000	1	2.0%
400	1	2.0%
19000	1	2.0%
30000	1	2.0%
102000	1	2.0%
Other values (10)	10	20.0%
(Missing)	26	52.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
400	1	2.0%
4000	2	4.0%
19000	1	2.0%
30000	1	2.0%
32000	2	4.0%
37000	1	2.0%
46000	1	2.0%
48000	1	2.0%
60000	1	2.0%
65000	1	2.0%

Value	Count	Frequency (%)
194400	1	2.0%
190000	1	2.0%
135000	1	2.0%
130000	3	6.0%
125000	1	2.0%
110000	1	2.0%
106960	1	2.0%
102000	1	2.0%
100000	1	2.0%
85000	1	2.0%

CompFreq
Categorical

HIGH CORRELATION MISSING

Distinct	3
Distinct (%)	11.5%
Missing	24
Missing (%)	48.0%
Memory size	528.0 B

Yearly	16
Monthly	9
Weekly	1

Length

Max length	7
Median length	6
Mean length	6.3461538
Min length	6

Characters and Unicode

Total characters	165
Distinct characters	13
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	3.8%

Sample

1st row	Yearly
2nd row	Monthly
3rd row	Yearly
4th row	Yearly
5th row	Yearly

Common Values

Value	Count	Frequency (%)
Yearly	16	32.0%
Monthly	9	18.0%
Weekly	1	2.0%
(Missing)	24	48.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
yearly	16	61.5%
monthly	9	34.6%
weekly	1	3.8%

Most occurring characters

Value	Count	Frequency (%)
l	26	15.8%
y	26	15.8%
e	18	10.9%
Y	16	9.7%
a	16	9.7%
r	16	9.7%
M	9	5.5%
o	9	5.5%
n	9	5.5%
t	9	5.5%
Other values (3)	11	6.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	139	84.2%
Uppercase Letter	26	15.8%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
l	26	18.7%
y	26	18.7%
e	18	12.9%
a	16	11.5%
r	16	11.5%
o	9	6.5%
n	9	6.5%
t	9	6.5%
h	9	6.5%
k	1	0.7%

Uppercase Letter

Value	Count	Frequency (%)
Y	16	61.5%
M	9	34.6%
W	1	3.8%

Most occurring scripts

Value	Count	Frequency (%)
Latin	165	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
l	26	15.8%
y	26	15.8%
e	18	10.9%
Y	16	9.7%
a	16	9.7%
r	16	9.7%
M	9	5.5%
o	9	5.5%
n	9	5.5%
t	9	5.5%
Other values (3)	11	6.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	165	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
l	26	15.8%
y	26	15.8%
e	18	10.9%
Y	16	9.7%
a	16	9.7%
r	16	9.7%
M	9	5.5%
o	9	5.5%
n	9	5.5%
t	9	5.5%
Other values (3)	11	6.7%

LanguageHaveWorkedWith
Categorical

HIGH CORRELATION MISSING UNIFORM

Distinct	45
Distinct (%)	97.8%
Missing	4
Missing (%)	8.0%
Memory size	528.0 B

JavaScript;TypeScript	2
C#;C++;HTML/CSS;Java;JavaScript;MATLAB;Python;SQL	1
Bash/Shell;Groovy;HTML/CSS;Java;JavaScript;SQL	1
C#;HTML/CSS;JavaScript;Rust;TypeScript	1
C;C++	1
Other values (40)	40

Length

Max length	64
Median length	42
Mean length	31.695652
Min length	3

Characters and Unicode

Total characters	1458
Distinct characters	42
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	44 ?
Unique (%)	95.7%

Sample

1st row	JavaScript;TypeScript
2nd row	C#;C++;HTML/CSS;JavaScript;Python
3rd row	C#;JavaScript;SQL;TypeScript
4th row	C#;HTML/CSS;JavaScript;SQL;Swift;TypeScript
5th row	C++;Lua

Common Values

Value	Count	Frequency (%)
JavaScript;TypeScript	2	4.0%
C#;C++;HTML/CSS;Java;JavaScript;MATLAB;Python;SQL	1	2.0%
Bash/Shell;Groovy;HTML/CSS;Java;JavaScript;SQL	1	2.0%
C#;HTML/CSS;JavaScript;Rust;TypeScript	1	2.0%
C;C++	1	2.0%
C#;JavaScript;PowerShell;SQL	1	2.0%
C#;HTML/CSS;JavaScript;SQL	1	2.0%
C++;Python	1	2.0%
C++;Go;Python	1	2.0%
HTML/CSS;JavaScript;Python;SQL;TypeScript	1	2.0%
Other values (35)	35	70.0%
(Missing)	4	8.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
javascript;typescript	2	4.3%
vba	1	2.2%
c#;c++;html/css;javascript;python	1	2.2%
c#;javascript;sql;typescript	1	2.2%
c#;html/css;javascript;sql;swift;typescript	1	2.2%
c++;lua	1	2.2%
c++;html/css;javascript;php;python;typescript	1	2.2%
c;c++;html/css;java;javascript;sql	1	2.2%
delphi;java;swift	1	2.2%
bash/shell;c#;html/css;javascript;powershell;sql	1	2.2%
Other values (35)	35	76.1%

Most occurring characters

Value	Count	Frequency (%)
;	172	11.8%
S	142	9.7%
a	101	6.9%
t	76	5.2%
p	66	4.5%
C	58	4.0%
r	58	4.0%
i	56	3.8%
L	55	3.8%
c	49	3.4%
Other values (32)	625	42.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	702	48.1%
Uppercase Letter	510	35.0%
Other Punctuation	222	15.2%
Math Symbol	24	1.6%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	101	14.4%
t	76	10.8%
p	66	9.4%
r	58	8.3%
i	56	8.0%
c	49	7.0%
v	44	6.3%
y	42	6.0%
h	40	5.7%
e	39	5.6%
Other values (11)	131	18.7%

Uppercase Letter

Value	Count	Frequency (%)
S	142	27.8%
C	58	11.4%
L	55	10.8%
T	45	8.8%
J	42	8.2%
P	40	7.8%
H	34	6.7%
M	27	5.3%
Q	26	5.1%
B	12	2.4%
Other values (7)	29	5.7%

Other Punctuation

Value	Count	Frequency (%)
;	172	77.5%
/	33	14.9%
#	17	7.7%

Math Symbol

Value	Count	Frequency (%)
+	24	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1212	83.1%
Common	246	16.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
S	142	11.7%
a	101	8.3%
t	76	6.3%
p	66	5.4%
C	58	4.8%
r	58	4.8%
i	56	4.6%
L	55	4.5%
c	49	4.0%
T	45	3.7%
Other values (28)	506	41.7%

Common

Value	Count	Frequency (%)
;	172	69.9%
/	33	13.4%
+	24	9.8%
#	17	6.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1458	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
;	172	11.8%
S	142	9.7%
a	101	6.9%
t	76	5.2%
p	66	4.5%
C	58	4.0%
r	58	4.0%
i	56	3.8%
L	55	3.8%
c	49	3.4%
Other values (32)	625	42.9%

LanguageWantToWorkWith
Categorical

HIGH CORRELATION MISSING UNIFORM

Distinct	43
Distinct (%)	95.6%
Missing	5
Missing (%)	10.0%
Memory size	528.0 B

TypeScript	2
Python	2
Rust;TypeScript	1
C#;Dart;Java;Kotlin;Swift;TypeScript	1
Bash/Shell;Groovy;HTML/CSS;Java;JavaScript;Python	1
Other values (38)	38

Length

Max length	79
Median length	36
Mean length	26.955556
Min length	3

Characters and Unicode

Total characters	1213
Distinct characters	43
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	41 ?
Unique (%)	91.1%

Sample

1st row	Rust;TypeScript
2nd row	C#;C++;HTML/CSS;JavaScript;TypeScript
3rd row	C#;SQL;TypeScript
4th row	C#;Elixir;F#;Go;JavaScript;Rust;TypeScript
5th row	Lua

Common Values

Value	Count	Frequency (%)
TypeScript	2	4.0%
Python	2	4.0%
Rust;TypeScript	1	2.0%
C#;Dart;Java;Kotlin;Swift;TypeScript	1	2.0%
Bash/Shell;Groovy;HTML/CSS;Java;JavaScript;Python	1	2.0%
HTML/CSS;Rust;TypeScript	1	2.0%
C++	1	2.0%
Go;Python	1	2.0%
HTML/CSS;JavaScript;Python;SQL	1	2.0%
Bash/Shell;Go;Python	1	2.0%
Other values (33)	33	66.0%
(Missing)	5	10.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
typescript	2	4.4%
python	2	4.4%
bash/shell;html/css;java;javascript;python;sql;typescript	1	2.2%
html/css;python;sql	1	2.2%
c++;go;html/css;javascript;lua;rust;typescript	1	2.2%
c#;c++;html/css;javascript;typescript	1	2.2%
c#;sql;typescript	1	2.2%
c#;elixir;f#;go;javascript;rust;typescript	1	2.2%
lua	1	2.2%
c;c#;c++;elixir;go;html/css;java;javascript;kotlin;python;rust;swift;typescript	1	2.2%
Other values (33)	33	73.3%

Most occurring characters

Value	Count	Frequency (%)
;	139	11.5%
S	104	8.6%
t	74	6.1%
a	72	5.9%
p	56	4.6%
i	55	4.5%
r	49	4.0%
y	44	3.6%
l	42	3.5%
h	39	3.2%
Other values (33)	539	44.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	649	53.5%
Uppercase Letter	372	30.7%
Other Punctuation	176	14.5%
Math Symbol	16	1.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
t	74	11.4%
a	72	11.1%
p	56	8.6%
i	55	8.5%
r	49	7.6%
y	44	6.8%
l	42	6.5%
h	39	6.0%
c	38	5.9%
o	38	5.9%
Other values (11)	142	21.9%

Uppercase Letter

Value	Count	Frequency (%)
S	104	28.0%
L	38	10.2%
T	36	9.7%
C	35	9.4%
P	26	7.0%
J	24	6.5%
H	20	5.4%
Q	18	4.8%
M	16	4.3%
B	11	3.0%
Other values (8)	44	11.8%

Other Punctuation

Value	Count	Frequency (%)
;	139	79.0%
/	25	14.2%
#	12	6.8%

Math Symbol

Value	Count	Frequency (%)
+	16	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1021	84.2%
Common	192	15.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
S	104	10.2%
t	74	7.2%
a	72	7.1%
p	56	5.5%
i	55	5.4%
r	49	4.8%
y	44	4.3%
l	42	4.1%
h	39	3.8%
c	38	3.7%
Other values (29)	448	43.9%

Common

Value	Count	Frequency (%)
;	139	72.4%
/	25	13.0%
+	16	8.3%
#	12	6.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1213	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
;	139	11.5%
S	104	8.6%
t	74	6.1%
a	72	5.9%
p	56	4.6%
i	55	4.5%
r	49	4.0%
y	44	3.6%
l	42	3.5%
h	39	3.2%
Other values (33)	539	44.4%

DatabaseHaveWorkedWith
Categorical

HIGH CORRELATION MISSING

Distinct	27
Distinct (%)	71.1%
Missing	12
Missing (%)	24.0%
Memory size	528.0 B

Microsoft SQL Server	5
PostgreSQL	4
MongoDB;MySQL	3
MySQL	3
PostgreSQL;Redis;SQLite	1
Other values (22)	22

Length

Max length	84
Median length	44.5
Mean length	25.710526
Min length	5

Characters and Unicode

Total characters	977
Distinct characters	36
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	23 ?
Unique (%)	60.5%

Sample

1st row	Microsoft SQL Server
2nd row	Microsoft SQL Server
3rd row	Cloud Firestore;Elasticsearch;Microsoft SQL Server;Firebase Realtime Database
4th row	Cloud Firestore;MongoDB;Firebase Realtime Database
5th row	MongoDB;MySQL

Common Values

Value	Count	Frequency (%)
Microsoft SQL Server	5	10.0%
PostgreSQL	4	8.0%
MongoDB;MySQL	3	6.0%
MySQL	3	6.0%
PostgreSQL;Redis;SQLite	1	2.0%
MongoDB;SQLite	1	2.0%
Microsoft SQL Server;MongoDB;MySQL;Oracle;PostgreSQL	1	2.0%
MongoDB;MySQL;SQLite	1	2.0%
Elasticsearch;MariaDB;PostgreSQL;Redis	1	2.0%
SQLite	1	2.0%
Other values (17)	17	34.0%
(Missing)	12	24.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
sql	13	17.8%
microsoft	10	13.7%
server	5	6.8%
postgresql	4	5.5%
realtime	3	4.1%
cloud	3	4.1%
mysql	3	4.1%
mongodb;mysql	3	4.1%
database	2	2.7%
server;firebase	1	1.4%
Other values (26)	26	35.6%

Most occurring characters

Value	Count	Frequency (%)
e	86	8.8%
o	76	7.8%
r	74	7.6%
S	67	6.9%
s	58	5.9%
;	55	5.6%
Q	54	5.5%
L	54	5.5%
t	51	5.2%
i	45	4.6%
Other values (26)	357	36.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	584	59.8%
Uppercase Letter	302	30.9%
Other Punctuation	55	5.6%
Space Separator	35	3.6%
Decimal Number	1	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	86	14.7%
o	76	13.0%
r	74	12.7%
s	58	9.9%
t	51	8.7%
i	45	7.7%
a	38	6.5%
g	28	4.8%
c	24	4.1%
y	17	2.9%
Other values (10)	87	14.9%

Uppercase Letter

Value	Count	Frequency (%)
S	67	22.2%
Q	54	17.9%
L	54	17.9%
M	44	14.6%
D	21	7.0%
B	17	5.6%
P	16	5.3%
R	10	3.3%
C	7	2.3%
F	6	2.0%
Other values (3)	6	2.0%

Other Punctuation

Value	Count	Frequency (%)
;	55	100.0%

Space Separator

Value	Count	Frequency (%)
	35	100.0%

Decimal Number

Value	Count	Frequency (%)
4	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	886	90.7%
Common	91	9.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	86	9.7%
o	76	8.6%
r	74	8.4%
S	67	7.6%
s	58	6.5%
Q	54	6.1%
L	54	6.1%
t	51	5.8%
i	45	5.1%
M	44	5.0%
Other values (23)	277	31.3%

Common

Value	Count	Frequency (%)
;	55	60.4%
	35	38.5%
4	1	1.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	977	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	86	8.8%
o	76	7.8%
r	74	7.6%
S	67	6.9%
s	58	5.9%
;	55	5.6%
Q	54	5.5%
L	54	5.5%
t	51	5.2%
i	45	4.6%
Other values (26)	357	36.5%

DatabaseWantToWorkWith
Categorical

HIGH CORRELATION MISSING

Distinct	25
Distinct (%)	78.1%
Missing	18
Missing (%)	36.0%
Memory size	528.0 B

Microsoft SQL Server	4
SQLite	3
PostgreSQL;Redis;SQLite	2
MySQL	2
MySQL;PostgreSQL;Redis;SQLite	1
Other values (20)	20

Length

Max length	84
Median length	38
Mean length	26.5625
Min length	5

Characters and Unicode

Total characters	850
Distinct characters	36
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	21 ?
Unique (%)	65.6%

Sample

1st row	Microsoft SQL Server
2nd row	Microsoft SQL Server
3rd row	Cloud Firestore;Elasticsearch;Firebase Realtime Database;Redis
4th row	MySQL;Oracle;PostgreSQL
5th row	Neo4j;PostgreSQL

Common Values

Value	Count	Frequency (%)
Microsoft SQL Server	4	8.0%
SQLite	3	6.0%
PostgreSQL;Redis;SQLite	2	4.0%
MySQL	2	4.0%
MySQL;PostgreSQL;Redis;SQLite	1	2.0%
MongoDB;MySQL;PostgreSQL;Firebase Realtime Database	1	2.0%
DynamoDB;Elasticsearch;Microsoft SQL Server;MongoDB;MySQL;PostgreSQL;Redis	1	2.0%
PostgreSQL;Redis	1	2.0%
Elasticsearch;MariaDB;PostgreSQL;Redis	1	2.0%
CouchDB;Elasticsearch;MySQL;PostgreSQL;Redis	1	2.0%
Other values (15)	15	30.0%
(Missing)	18	36.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
sql	7	12.5%
microsoft	5	8.9%
server	4	7.1%
realtime	4	7.1%
sqlite	3	5.4%
postgresql;redis;sqlite	2	3.6%
mysql	2	3.6%
database	2	3.6%
cloud	2	3.6%
postgresql	1	1.8%
Other values (24)	24	42.9%

Most occurring characters

Value	Count	Frequency (%)
e	84	9.9%
s	62	7.3%
r	59	6.9%
o	53	6.2%
t	50	5.9%
;	49	5.8%
S	48	5.6%
a	47	5.5%
i	46	5.4%
Q	41	4.8%
Other values (26)	311	36.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	538	63.3%
Uppercase Letter	237	27.9%
Other Punctuation	49	5.8%
Space Separator	24	2.8%
Decimal Number	2	0.2%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	84	15.6%
s	62	11.5%
r	59	11.0%
o	53	9.9%
t	50	9.3%
a	47	8.7%
i	46	8.6%
c	25	4.6%
g	24	4.5%
l	15	2.8%
Other values (10)	73	13.6%

Uppercase Letter

Value	Count	Frequency (%)
S	48	20.3%
Q	41	17.3%
L	41	17.3%
M	26	11.0%
D	17	7.2%
P	17	7.2%
R	14	5.9%
B	12	5.1%
E	8	3.4%
F	6	2.5%
Other values (3)	7	3.0%

Other Punctuation

Value	Count	Frequency (%)
;	49	100.0%

Space Separator

Value	Count	Frequency (%)
	24	100.0%

Decimal Number

Value	Count	Frequency (%)
4	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	775	91.2%
Common	75	8.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	84	10.8%
s	62	8.0%
r	59	7.6%
o	53	6.8%
t	50	6.5%
S	48	6.2%
a	47	6.1%
i	46	5.9%
Q	41	5.3%
L	41	5.3%
Other values (23)	244	31.5%

Common

Value	Count	Frequency (%)
;	49	65.3%
	24	32.0%
4	2	2.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	850	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	84	9.9%
s	62	7.3%
r	59	6.9%
o	53	6.2%
t	50	5.9%
;	49	5.8%
S	48	5.6%
a	47	5.5%
i	46	5.4%
Q	41	4.8%
Other values (26)	311	36.6%

PlatformHaveWorkedWith
Categorical

HIGH CORRELATION MISSING

Distinct	20
Distinct (%)	71.4%
Missing	22
Missing (%)	44.0%
Memory size	528.0 B

AWS;Microsoft Azure	4
Microsoft Azure	3
AWS	3
AWS;Google Cloud	2
DigitalOcean;Firebase	1
Other values (15)	15

Length

Max length	35
Median length	25.5
Mean length	17.785714
Min length	3

Characters and Unicode

Total characters	498
Distinct characters	32
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	16 ?
Unique (%)	57.1%

Sample

1st row	Firebase;Microsoft Azure
2nd row	AWS;Google Cloud;Heroku
3rd row	DigitalOcean;Firebase
4th row	AWS;Microsoft Azure
5th row	AWS;Microsoft Azure

Common Values

Value	Count	Frequency (%)
AWS;Microsoft Azure	4	8.0%
Microsoft Azure	3	6.0%
AWS	3	6.0%
AWS;Google Cloud	2	4.0%
DigitalOcean;Firebase	1	2.0%
AWS;Heroku	1	2.0%
AWS;DigitalOcean;Heroku	1	2.0%
AWS;Firebase;Google Cloud;Heroku	1	2.0%
Google Cloud;VMware	1	2.0%
Firebase;Microsoft Azure	1	2.0%
Other values (10)	10	20.0%
(Missing)	22	44.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
azure	10	20.8%
aws;microsoft	4	8.3%
aws;google	4	8.3%
microsoft	4	8.3%
google	3	6.2%
aws	3	6.2%
cloud	2	4.2%
cloud;ovh;vmware	2	4.2%
cloud;heroku	2	4.2%
aws;managed	1	2.1%
Other values (13)	13	27.1%

Most occurring characters

Value	Count	Frequency (%)
o	54	10.8%
e	42	8.4%
r	37	7.4%
;	31	6.2%
A	29	5.8%
u	25	5.0%
i	21	4.2%
	20	4.0%
S	18	3.6%
l	18	3.6%
Other values (22)	203	40.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	319	64.1%
Uppercase Letter	128	25.7%
Other Punctuation	31	6.2%
Space Separator	20	4.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	54	16.9%
e	42	13.2%
r	37	11.6%
u	25	7.8%
i	21	6.6%
l	18	5.6%
s	16	5.0%
a	15	4.7%
t	14	4.4%
c	13	4.1%
Other values (8)	64	20.1%

Uppercase Letter

Value	Count	Frequency (%)
A	29	22.7%
S	18	14.1%
W	18	14.1%
M	17	13.3%
H	10	7.8%
V	8	6.2%
G	8	6.2%
C	8	6.2%
O	5	3.9%
F	4	3.1%
Other values (2)	3	2.3%

Other Punctuation

Value	Count	Frequency (%)
;	31	100.0%

Space Separator

Value	Count	Frequency (%)
	20	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	447	89.8%
Common	51	10.2%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	54	12.1%
e	42	9.4%
r	37	8.3%
A	29	6.5%
u	25	5.6%
i	21	4.7%
S	18	4.0%
l	18	4.0%
W	18	4.0%
M	17	3.8%
Other values (20)	168	37.6%

Common

Value	Count	Frequency (%)
;	31	60.8%
	20	39.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	498	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	54	10.8%
e	42	8.4%
r	37	7.4%
;	31	6.2%
A	29	5.8%
u	25	5.0%
i	21	4.2%
	20	4.0%
S	18	3.6%
l	18	3.6%
Other values (22)	203	40.8%

PlatformWantToWorkWith
Categorical

HIGH CORRELATION MISSING

Distinct	14
Distinct (%)	70.0%
Missing	30
Missing (%)	60.0%
Memory size	528.0 B

AWS	6
Google Cloud;OVH;VMware	2
Firebase;Microsoft Azure	1
DigitalOcean;Firebase;Microsoft Azure;VMware	1
DigitalOcean;Firebase	1
Other values (9)	9

Length

Max length	44
Median length	29
Mean length	17.75
Min length	3

Characters and Unicode

Total characters	355
Distinct characters	32
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	12 ?
Unique (%)	60.0%

Sample

1st row	Firebase;Microsoft Azure
2nd row	DigitalOcean;Firebase;Microsoft Azure;VMware
3rd row	DigitalOcean;Firebase
4th row	Microsoft Azure
5th row	AWS;DigitalOcean;Firebase;Linode

Common Values

Value	Count	Frequency (%)
AWS	6	12.0%
Google Cloud;OVH;VMware	2	4.0%
Firebase;Microsoft Azure	1	2.0%
DigitalOcean;Firebase;Microsoft Azure;VMware	1	2.0%
DigitalOcean;Firebase	1	2.0%
Microsoft Azure	1	2.0%
AWS;DigitalOcean;Firebase;Linode	1	2.0%
AWS;Firebase;Google Cloud;Heroku	1	2.0%
AWS;Google Cloud	1	2.0%
AWS;Microsoft Azure	1	2.0%
Other values (4)	4	8.0%
(Missing)	30	60.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
aws	6	19.4%
azure	5	16.1%
cloud;ovh;vmware	2	6.5%
google	2	6.5%
aws;google	2	6.5%
cloud;heroku	1	3.2%
vmware	1	3.2%
aws;heroku;linode	1	3.2%
cloud;linode;microsoft	1	3.2%
aws;microsoft	1	3.2%
Other values (9)	9	29.0%

Most occurring characters

Value	Count	Frequency (%)
e	34	9.6%
o	33	9.3%
r	24	6.8%
;	24	6.8%
i	20	5.6%
A	19	5.4%
a	15	4.2%
u	14	3.9%
W	13	3.7%
S	13	3.7%
Other values (22)	146	41.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	228	64.2%
Uppercase Letter	92	25.9%
Other Punctuation	24	6.8%
Space Separator	11	3.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	34	14.9%
o	33	14.5%
r	24	10.5%
i	20	8.8%
a	15	6.6%
u	14	6.1%
l	13	5.7%
s	11	4.8%
t	9	3.9%
c	9	3.9%
Other values (8)	46	20.2%

Uppercase Letter

Value	Count	Frequency (%)
A	19	20.7%
W	13	14.1%
S	13	14.1%
M	10	10.9%
V	6	6.5%
H	5	5.4%
G	5	5.4%
F	5	5.4%
C	5	5.4%
O	5	5.4%
Other values (2)	6	6.5%

Other Punctuation

Value	Count	Frequency (%)
;	24	100.0%

Space Separator

Value	Count	Frequency (%)
	11	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	320	90.1%
Common	35	9.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	34	10.6%
o	33	10.3%
r	24	7.5%
i	20	6.2%
A	19	5.9%
a	15	4.7%
u	14	4.4%
W	13	4.1%
S	13	4.1%
l	13	4.1%
Other values (20)	122	38.1%

Common

Value	Count	Frequency (%)
;	24	68.6%
	11	31.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	355	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	34	9.6%
o	33	9.3%
r	24	6.8%
;	24	6.8%
i	20	5.6%
A	19	5.4%
a	15	4.2%
u	14	3.9%
W	13	3.7%
S	13	3.7%
Other values (22)	146	41.1%

WebframeHaveWorkedWith
Categorical

HIGH CORRELATION MISSING UNIFORM

Distinct	30
Distinct (%)	90.9%
Missing	17
Missing (%)	34.0%
Memory size	528.0 B

ASP.NET;ASP.NET Core	2
jQuery;Node.js	2
Node.js	2
Flask;jQuery;Node.js;Nuxt.js;React.js;Ruby on Rails;Vue.js	1
ASP.NET Core	1
Other values (25)	25

Length

Max length	58
Median length	34
Mean length	25.272727
Min length	5

Characters and Unicode

Total characters	834
Distinct characters	39
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	27 ?
Unique (%)	81.8%

Sample

1st row	Angular.js
2nd row	ASP.NET;ASP.NET Core
3rd row	Angular;ASP.NET;ASP.NET Core ;jQuery;Node.js
4th row	Angular;Next.js;Node.js;React.js;Svelte;Vue.js
5th row	jQuery;Node.js

Common Values

Value	Count	Frequency (%)
ASP.NET;ASP.NET Core	2	4.0%
jQuery;Node.js	2	4.0%
Node.js	2	4.0%
Flask;jQuery;Node.js;Nuxt.js;React.js;Ruby on Rails;Vue.js	1	2.0%
ASP.NET Core	1	2.0%
ASP.NET	1	2.0%
Django;FastAPI;React.js	1	2.0%
Angular;Angular.js;Django;Flask;jQuery;Node.js	1	2.0%
ASP.NET;ASP.NET Core ;jQuery	1	2.0%
Flask	1	2.0%
Other values (20)	20	40.0%
(Missing)	17	34.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
core	11	18.6%
asp.net;asp.net	5	8.5%
on	4	6.8%
asp.net	4	6.8%
jquery;node.js	3	5.1%
react.js	3	5.1%
rails	2	3.4%
angular;asp.net	2	3.4%
jquery	2	3.4%
rails;vue.js	2	3.4%
Other values (20)	21	35.6%

Most occurring characters

Value	Count	Frequency (%)
e	67	8.0%
;	66	7.9%
.	59	7.1%
s	58	7.0%
j	56	6.7%
r	38	4.6%
a	37	4.4%
N	37	4.4%
u	37	4.4%
o	35	4.2%
Other values (29)	344	41.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	469	56.2%
Uppercase Letter	210	25.2%
Other Punctuation	125	15.0%
Space Separator	30	3.6%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	67	14.3%
s	58	12.4%
j	56	11.9%
r	38	8.1%
a	37	7.9%
u	37	7.9%
o	35	7.5%
l	21	4.5%
n	19	4.1%
t	17	3.6%
Other values (11)	84	17.9%

Uppercase Letter

Value	Count	Frequency (%)
N	37	17.6%
A	31	14.8%
E	21	10.0%
P	21	10.0%
S	19	9.0%
R	18	8.6%
T	18	8.6%
Q	12	5.7%
C	11	5.2%
V	9	4.3%
Other values (5)	13	6.2%

Other Punctuation

Value	Count	Frequency (%)
;	66	52.8%
.	59	47.2%

Space Separator

Value	Count	Frequency (%)
	30	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	679	81.4%
Common	155	18.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	67	9.9%
s	58	8.5%
j	56	8.2%
r	38	5.6%
a	37	5.4%
N	37	5.4%
u	37	5.4%
o	35	5.2%
A	31	4.6%
E	21	3.1%
Other values (26)	262	38.6%

Common

Value	Count	Frequency (%)
;	66	42.6%
.	59	38.1%
	30	19.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	834	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	67	8.0%
;	66	7.9%
.	59	7.1%
s	58	7.0%
j	56	6.7%
r	38	4.6%
a	37	4.4%
N	37	4.4%
u	37	4.4%
o	35	4.2%
Other values (29)	344	41.2%

WebframeWantToWorkWith
Categorical

HIGH CORRELATION MISSING UNIFORM

Distinct	27
Distinct (%)	96.4%
Missing	22
Missing (%)	44.0%
Memory size	528.0 B

React.js	2
ASP.NET Core	1
Node.js;React.js;Vue.js	1
Angular;Angular.js;ASP.NET Core ;Blazor;Django;Node.js;React.js;Ruby on Rails	1
Vue.js	1
Other values (22)	22

Length

Max length	77
Median length	35.5
Mean length	26.607143
Min length	6

Characters and Unicode

Total characters	745
Distinct characters	42
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	26 ?
Unique (%)	92.9%

Sample

1st row	Angular;Angular.js
2nd row	ASP.NET;ASP.NET Core
3rd row	Angular;ASP.NET Core ;Blazor;Node.js
4th row	Django;Flask;Gatsby;jQuery;Next.js;Node.js;React.js;Svelte;Vue.js
5th row	Angular;Angular.js;Next.js;Vue.js

Common Values

Value	Count	Frequency (%)
React.js	2	4.0%
ASP.NET Core	1	2.0%
Node.js;React.js;Vue.js	1	2.0%
Angular;Angular.js;ASP.NET Core ;Blazor;Django;Node.js;React.js;Ruby on Rails	1	2.0%
Vue.js	1	2.0%
Flask;Ruby on Rails	1	2.0%
jQuery;Node.js;Nuxt.js;Ruby on Rails;Vue.js	1	2.0%
Django;FastAPI;React.js	1	2.0%
Django	1	2.0%
Angular;ASP.NET Core ;Blazor;Vue.js	1	2.0%
Other values (17)	17	34.0%
(Missing)	22	44.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
core	8	16.3%
on	4	8.2%
angular;asp.net	3	6.1%
react.js	2	4.1%
rails	2	4.1%
asp.net;asp.net	2	4.1%
asp.net	2	4.1%
blazor	2	4.1%
vue.js	1	2.0%
flask;ruby	1	2.0%
Other values (22)	22	44.9%

Most occurring characters

Value	Count	Frequency (%)
;	61	8.2%
s	57	7.7%
e	54	7.2%
.	53	7.1%
j	51	6.8%
a	41	5.5%
o	34	4.6%
u	32	4.3%
N	28	3.8%
r	28	3.8%
Other values (32)	306	41.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	447	60.0%
Uppercase Letter	160	21.5%
Other Punctuation	114	15.3%
Space Separator	24	3.2%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
s	57	12.8%
e	54	12.1%
j	51	11.4%
a	41	9.2%
o	34	7.6%
u	32	7.2%
r	28	6.3%
t	25	5.6%
l	23	5.1%
n	21	4.7%
Other values (14)	81	18.1%

Uppercase Letter

Value	Count	Frequency (%)
N	28	17.5%
A	23	14.4%
R	19	11.9%
P	14	8.8%
S	13	8.1%
E	12	7.5%
V	11	6.9%
T	10	6.2%
C	8	5.0%
D	5	3.1%
Other values (5)	17	10.6%

Other Punctuation

Value	Count	Frequency (%)
;	61	53.5%
.	53	46.5%

Space Separator

Value	Count	Frequency (%)
	24	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	607	81.5%
Common	138	18.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
s	57	9.4%
e	54	8.9%
j	51	8.4%
a	41	6.8%
o	34	5.6%
u	32	5.3%
N	28	4.6%
r	28	4.6%
t	25	4.1%
l	23	3.8%
Other values (29)	234	38.6%

Common

Value	Count	Frequency (%)
;	61	44.2%
.	53	38.4%
	24	17.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	745	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
;	61	8.2%
s	57	7.7%
e	54	7.2%
.	53	7.1%
j	51	6.8%
a	41	5.5%
o	34	4.6%
u	32	4.3%
N	28	3.8%
r	28	3.8%
Other values (32)	306	41.1%

MiscTechHaveWorkedWith
Categorical

HIGH CORRELATION MISSING

Distinct	17
Distinct (%)	65.4%
Missing	24
Missing (%)	48.0%
Memory size	528.0 B

.NET	10
Qt	1
.NET;NumPy;Spring;Torch/PyTorch	1
Keras;NumPy;Pandas;Scikit-learn;TensorFlow	1
.NET;Xamarin	1
Other values (12)	12

Length

Max length	87
Median length	48.5
Mean length	17.615385
Min length	2

Characters and Unicode

Total characters	458
Distinct characters	38
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	16 ?
Unique (%)	61.5%

Sample

1st row	Pandas
2nd row	.NET
3rd row	.NET
4th row	.NET
5th row	.NET;Keras;NumPy;Pandas;Scikit-learn;TensorFlow;Torch/PyTorch;Hugging Face Transformers

Common Values

Value	Count	Frequency (%)
.NET	10	20.0%
Qt	1	2.0%
.NET;NumPy;Spring;Torch/PyTorch	1	2.0%
Keras;NumPy;Pandas;Scikit-learn;TensorFlow	1	2.0%
.NET;Xamarin	1	2.0%
Spring	1	2.0%
NumPy;Scikit-learn;Torch/PyTorch	1	2.0%
NumPy;Pandas;Scikit-learn	1	2.0%
Apache Kafka;Flutter	1	2.0%
Pandas	1	2.0%
Other values (7)	7	14.0%
(Missing)	24	48.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
net	10	30.3%
apache	2	6.1%
native	2	6.1%
keras;numpy;pandas;scikit-learn;spring;tensorflow	1	3.0%
transformers	1	3.0%
face	1	3.0%
net;keras;numpy;pandas;scikit-learn;tensorflow;torch/pytorch;hugging	1	3.0%
torch/pytorch	1	3.0%
spark;numpy;pandas;tidyverse	1	3.0%
kafka;apache	1	3.0%
Other values (12)	12	36.4%

Most occurring characters

Value	Count	Frequency (%)
a	38	8.3%
;	31	6.8%
r	30	6.6%
T	26	5.7%
e	24	5.2%
N	23	5.0%
n	22	4.8%
c	20	4.4%
P	19	4.1%
i	18	3.9%
Other values (28)	207	45.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	289	63.1%
Uppercase Letter	109	23.8%
Other Punctuation	48	10.5%
Space Separator	7	1.5%
Dash Punctuation	5	1.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	38	13.1%
r	30	10.4%
e	24	8.3%
n	22	7.6%
c	20	6.9%
i	18	6.2%
o	16	5.5%
s	16	5.5%
t	13	4.5%
y	13	4.5%
Other values (11)	79	27.3%

Uppercase Letter

Value	Count	Frequency (%)
T	26	23.9%
N	23	21.1%
P	19	17.4%
E	14	12.8%
S	9	8.3%
F	5	4.6%
K	5	4.6%
A	3	2.8%
R	2	1.8%
Q	1	0.9%
Other values (2)	2	1.8%

Other Punctuation

Value	Count	Frequency (%)
;	31	64.6%
.	13	27.1%
/	4	8.3%

Space Separator

Value	Count	Frequency (%)
	7	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	5	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	398	86.9%
Common	60	13.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	38	9.5%
r	30	7.5%
T	26	6.5%
e	24	6.0%
N	23	5.8%
n	22	5.5%
c	20	5.0%
P	19	4.8%
i	18	4.5%
o	16	4.0%
Other values (23)	162	40.7%

Common

Value	Count	Frequency (%)
;	31	51.7%
.	13	21.7%
	7	11.7%
-	5	8.3%
/	4	6.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	458	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	38	8.3%
;	31	6.8%
r	30	6.6%
T	26	5.7%
e	24	5.2%
N	23	5.0%
n	22	4.8%
c	20	4.4%
P	19	4.1%
i	18	3.9%
Other values (28)	207	45.2%

MiscTechWantToWorkWith
Categorical

HIGH CORRELATION MISSING

Distinct	15
Distinct (%)	75.0%
Missing	30
Missing (%)	60.0%
Memory size	528.0 B

.NET	4
Flutter	3
.NET;Apache Kafka	1
Keras;NumPy;Pandas;Scikit-learn;TensorFlow;Torch/PyTorch;Hugging Face Transformers	1
Torch/PyTorch	1
Other values (10)	10

Length

Max length	82
Median length	39.5
Mean length	19.9
Min length	4

Characters and Unicode

Total characters	398
Distinct characters	37
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	13 ?
Unique (%)	65.0%

Sample

1st row	.NET
2nd row	.NET
3rd row	.NET;Apache Kafka
4th row	Keras;NumPy;Pandas;Scikit-learn;TensorFlow;Torch/PyTorch;Hugging Face Transformers
5th row	Torch/PyTorch

Common Values

Value	Count	Frequency (%)
.NET	4	8.0%
Flutter	3	6.0%
.NET;Apache Kafka	1	2.0%
Keras;NumPy;Pandas;Scikit-learn;TensorFlow;Torch/PyTorch;Hugging Face Transformers	1	2.0%
Torch/PyTorch	1	2.0%
Pandas	1	2.0%
Electron	1	2.0%
Keras;NumPy;Pandas;Scikit-learn;TensorFlow	1	2.0%
NumPy;Pandas	1	2.0%
Apache Kafka;Flutter	1	2.0%
Other values (5)	5	10.0%
(Missing)	30	60.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
net	4	14.8%
flutter	3	11.1%
face	2	7.4%
transformers	2	7.4%
apache	1	3.7%
native	1	3.7%
net;react	1	3.7%
keras;numpy;pandas;scikit-learn;tensorflow;hugging	1	3.7%
numpy;scikit-learn;torch/pytorch	1	3.7%
xamarin	1	3.7%
Other values (10)	10	37.0%

Most occurring characters

Value	Count	Frequency (%)
r	32	8.0%
a	31	7.8%
e	24	6.0%
;	24	6.0%
n	20	5.0%
T	20	5.0%
o	19	4.8%
c	18	4.5%
s	16	4.0%
t	15	3.8%
Other values (27)	179	45.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	272	68.3%
Uppercase Letter	81	20.4%
Other Punctuation	34	8.5%
Space Separator	7	1.8%
Dash Punctuation	4	1.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
r	32	11.8%
a	31	11.4%
e	24	8.8%
n	20	7.4%
o	19	7.0%
c	18	6.6%
s	16	5.9%
t	15	5.5%
l	13	4.8%
i	13	4.8%
Other values (11)	71	26.1%

Uppercase Letter

Value	Count	Frequency (%)
T	20	24.7%
P	15	18.5%
N	13	16.0%
F	10	12.3%
E	7	8.6%
K	5	6.2%
S	5	6.2%
H	2	2.5%
A	2	2.5%
X	1	1.2%

Other Punctuation

Value	Count	Frequency (%)
;	24	70.6%
.	6	17.6%
/	4	11.8%

Space Separator

Value	Count	Frequency (%)
	7	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	4	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	353	88.7%
Common	45	11.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
r	32	9.1%
a	31	8.8%
e	24	6.8%
n	20	5.7%
T	20	5.7%
o	19	5.4%
c	18	5.1%
s	16	4.5%
t	15	4.2%
P	15	4.2%
Other values (22)	143	40.5%

Common

Value	Count	Frequency (%)
;	24	53.3%
	7	15.6%
.	6	13.3%
/	4	8.9%
-	4	8.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	398	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
r	32	8.0%
a	31	7.8%
e	24	6.0%
;	24	6.0%
n	20	5.0%
T	20	5.0%
o	19	4.8%
c	18	4.5%
s	16	4.0%
t	15	3.8%
Other values (27)	179	45.0%

ToolsTechHaveWorkedWith
Categorical

HIGH CORRELATION MISSING

Distinct	18
Distinct (%)	60.0%
Missing	20
Missing (%)	40.0%
Memory size	528.0 B

npm	6
Docker	3
Docker;npm;Yarn	3
Docker;Homebrew;npm;Yarn	2
Docker;npm	2
Other values (13)	14

Length

Max length	36
Median length	26
Mean length	15.066667
Min length	3

Characters and Unicode

Total characters	452
Distinct characters	24
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	12 ?
Unique (%)	40.0%

Sample

1st row	npm
2nd row	Homebrew
3rd row	Homebrew;npm
4th row	npm
5th row	Docker;npm;Terraform

Common Values

Value	Count	Frequency (%)
npm	6	12.0%
Docker	3	6.0%
Docker;npm;Yarn	3	6.0%
Docker;Homebrew;npm;Yarn	2	4.0%
Docker;npm	2	4.0%
Docker;Homebrew;Kubernetes	2	4.0%
Docker;npm;Terraform	1	2.0%
Homebrew;npm	1	2.0%
Homebrew	1	2.0%
Docker;Kubernetes	1	2.0%
Other values (8)	8	16.0%
(Missing)	20	40.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
npm	6	20.0%
docker;npm;yarn	3	10.0%
docker	3	10.0%
docker;homebrew;npm;yarn	2	6.7%
docker;npm	2	6.7%
docker;homebrew;kubernetes	2	6.7%
docker;kubernetes;npm	1	3.3%
docker;homebrew;kubernetes;npm;yarn	1	3.3%
npm;yarn	1	3.3%
ansible;docker;terraform	1	3.3%
Other values (8)	8	26.7%

Most occurring characters

Value	Count	Frequency (%)
e	63	13.9%
r	57	12.6%
;	42	9.3%
n	40	8.8%
m	34	7.5%
o	32	7.1%
p	22	4.9%
D	20	4.4%
c	20	4.4%
k	20	4.4%
Other values (14)	102	22.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	360	79.6%
Uppercase Letter	50	11.1%
Other Punctuation	42	9.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	63	17.5%
r	57	15.8%
n	40	11.1%
m	34	9.4%
o	32	8.9%
p	22	6.1%
c	20	5.6%
k	20	5.6%
b	17	4.7%
a	13	3.6%
Other values (7)	42	11.7%

Uppercase Letter

Value	Count	Frequency (%)
D	20	40.0%
Y	8	16.0%
H	7	14.0%
K	7	14.0%
T	5	10.0%
A	3	6.0%

Other Punctuation

Value	Count	Frequency (%)
;	42	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	410	90.7%
Common	42	9.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	63	15.4%
r	57	13.9%
n	40	9.8%
m	34	8.3%
o	32	7.8%
p	22	5.4%
D	20	4.9%
c	20	4.9%
k	20	4.9%
b	17	4.1%
Other values (13)	85	20.7%

Common

Value	Count	Frequency (%)
;	42	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	452	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	63	13.9%
r	57	12.6%
;	42	9.3%
n	40	8.8%
m	34	7.5%
o	32	7.1%
p	22	4.9%
D	20	4.4%
c	20	4.4%
k	20	4.4%
Other values (14)	102	22.6%

ToolsTechWantToWorkWith
Categorical

HIGH CORRELATION MISSING

Distinct	15
Distinct (%)	57.7%
Missing	24
Missing (%)	48.0%
Memory size	528.0 B

Docker	5
Docker;Kubernetes	3
npm	3
Docker;npm;Yarn	2
Docker;npm	2
Other values (10)	11

Length

Max length	43
Median length	21
Mean length	15.961538
Min length	3

Characters and Unicode

Total characters	415
Distinct characters	30
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	9 ?
Unique (%)	34.6%

Sample

1st row	Docker;Kubernetes
2nd row	Homebrew
3rd row	npm
4th row	Unity 3D;Yarn
5th row	Docker;Terraform

Common Values

Value	Count	Frequency (%)
Docker	5	10.0%
Docker;Kubernetes	3	6.0%
npm	3	6.0%
Docker;npm;Yarn	2	4.0%
Docker;npm	2	4.0%
Ansible;Docker;Kubernetes;Terraform	2	4.0%
Homebrew	1	2.0%
Unity 3D;Yarn	1	2.0%
Docker;Terraform	1	2.0%
Docker;Homebrew;Kubernetes;Pulumi;Terraform	1	2.0%
Other values (5)	5	10.0%
(Missing)	24	48.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
docker	5	18.5%
docker;kubernetes	3	11.1%
npm	3	11.1%
docker;npm;yarn	2	7.4%
docker;npm	2	7.4%
ansible;docker;kubernetes;terraform	2	7.4%
homebrew	1	3.7%
unity	1	3.7%
3d;yarn	1	3.7%
docker;terraform	1	3.7%
Other values (6)	6	22.2%

Most occurring characters

Value	Count	Frequency (%)
e	64	15.4%
r	56	13.5%
;	33	8.0%
o	31	7.5%
n	27	6.5%
D	21	5.1%
c	20	4.8%
k	20	4.8%
m	20	4.8%
b	16	3.9%
Other values (20)	107	25.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	329	79.3%
Uppercase Letter	51	12.3%
Other Punctuation	33	8.0%
Space Separator	1	0.2%
Decimal Number	1	0.2%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	64	19.5%
r	56	17.0%
o	31	9.4%
n	27	8.2%
c	20	6.1%
k	20	6.1%
m	20	6.1%
b	16	4.9%
s	12	3.6%
u	11	3.3%
Other values (8)	52	15.8%

Uppercase Letter

Value	Count	Frequency (%)
D	21	41.2%
K	9	17.6%
T	6	11.8%
Y	5	9.8%
H	4	7.8%
A	3	5.9%
U	1	2.0%
P	1	2.0%
F	1	2.0%

Other Punctuation

Value	Count	Frequency (%)
;	33	100.0%

Space Separator

Value	Count	Frequency (%)
	1	100.0%

Decimal Number

Value	Count	Frequency (%)
3	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	380	91.6%
Common	35	8.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	64	16.8%
r	56	14.7%
o	31	8.2%
n	27	7.1%
D	21	5.5%
c	20	5.3%
k	20	5.3%
m	20	5.3%
b	16	4.2%
s	12	3.2%
Other values (17)	93	24.5%

Common

Value	Count	Frequency (%)
;	33	94.3%
	1	2.9%
3	1	2.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	415	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	64	15.4%
r	56	13.5%
;	33	8.0%
o	31	7.5%
n	27	6.5%
D	21	5.1%
c	20	4.8%
k	20	4.8%
m	20	4.8%
b	16	3.9%
Other values (20)	107	25.8%

NEWCollabToolsHaveWorkedWith
Categorical

HIGH CORRELATION MISSING

Distinct	37
Distinct (%)	78.7%
Missing	3
Missing (%)	6.0%
Memory size	528.0 B

Visual Studio Code	6
Notepad++;Visual Studio;Visual Studio Code	3
Visual Studio	2
Visual Studio;Visual Studio Code	2
Rider;Visual Studio;Visual Studio Code	2
Other values (32)	32

Length

Max length	86
Median length	48
Mean length	35.085106
Min length	9

Characters and Unicode

Total characters	1649
Distinct characters	42
Distinct categories	7 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	32 ?
Unique (%)	68.1%

Sample

1st row	Notepad++;Visual Studio
2nd row	Notepad++;Visual Studio;Visual Studio Code
3rd row	Notepad++;Visual Studio;Visual Studio Code;Xcode
4th row	Visual Studio Code;Xcode
5th row	Atom;IntelliJ;Notepad++;PyCharm;Sublime Text;Visual Studio Code

Common Values

Value	Count	Frequency (%)
Visual Studio Code	6	12.0%
Notepad++;Visual Studio;Visual Studio Code	3	6.0%
Visual Studio	2	4.0%
Visual Studio;Visual Studio Code	2	4.0%
Rider;Visual Studio;Visual Studio Code	2	4.0%
Notepad++;Rider;Visual Studio;Visual Studio Code	1	2.0%
CLion;IntelliJ;Nano;Notepad++;PyCharm;Vim;Visual Studio Code	1	2.0%
IPython/Jupyter;PyCharm;Vim;Visual Studio Code	1	2.0%
IPython/Jupyter;Nano;PyCharm;Sublime Text	1	2.0%
Android Studio;Eclipse;IntelliJ;Notepad++;PyCharm;Vim;Visual Studio;Visual Studio Code	1	2.0%
Other values (27)	27	54.0%
(Missing)	3	6.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
studio	40	28.2%
code	29	20.4%
studio;visual	13	9.2%
visual	11	7.7%
notepad++;visual	6	4.2%
code;xcode	3	2.1%
android	3	2.1%
rider;visual	2	1.4%
text;visual	2	1.4%
ipython/jupyter;neovim;visual	1	0.7%
Other values (32)	32	22.5%

Most occurring characters

Value	Count	Frequency (%)
i	158	9.6%
o	133	8.1%
d	121	7.3%
u	118	7.2%
t	108	6.5%
;	98	5.9%
e	96	5.8%
	95	5.8%
l	93	5.6%
a	83	5.0%
Other values (32)	546	33.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1133	68.7%
Uppercase Letter	279	16.9%
Other Punctuation	104	6.3%
Space Separator	95	5.8%
Math Symbol	36	2.2%
Open Punctuation	1	0.1%
Close Punctuation	1	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
i	158	13.9%
o	133	11.7%
d	121	10.7%
u	118	10.4%
t	108	9.5%
e	96	8.5%
l	93	8.2%
a	83	7.3%
s	62	5.5%
n	32	2.8%
Other values (9)	129	11.4%

Uppercase Letter

Value	Count	Frequency (%)
V	63	22.6%
S	61	21.9%
C	43	15.4%
N	25	9.0%
J	20	7.2%
I	20	7.2%
P	12	4.3%
E	8	2.9%
A	7	2.5%
R	6	2.2%
Other values (6)	14	5.0%

Other Punctuation

Value	Count	Frequency (%)
;	98	94.2%
/	5	4.8%
,	1	1.0%

Space Separator

Value	Count	Frequency (%)
	95	100.0%

Math Symbol

Value	Count	Frequency (%)
+	36	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	1	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1412	85.6%
Common	237	14.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
i	158	11.2%
o	133	9.4%
d	121	8.6%
u	118	8.4%
t	108	7.6%
e	96	6.8%
l	93	6.6%
a	83	5.9%
V	63	4.5%
s	62	4.4%
Other values (25)	377	26.7%

Common

Value	Count	Frequency (%)
;	98	41.4%
	95	40.1%
+	36	15.2%
/	5	2.1%
(	1	0.4%
,	1	0.4%
)	1	0.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1649	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
i	158	9.6%
o	133	8.1%
d	121	7.3%
u	118	7.2%
t	108	6.5%
;	98	5.9%
e	96	5.8%
	95	5.8%
l	93	5.6%
a	83	5.0%
Other values (32)	546	33.1%

NEWCollabToolsWantToWorkWith
Categorical

HIGH CORRELATION MISSING

Distinct	30
Distinct (%)	73.2%
Missing	9
Missing (%)	18.0%
Memory size	528.0 B

Visual Studio Code	9
Notepad++;Visual Studio;Visual Studio Code	2
Visual Studio;Visual Studio Code	2
IPython/Jupyter;PyCharm;Vim	2
IntelliJ;PyCharm;Vim	1
Other values (25)	25

Length

Max length	72
Median length	41
Mean length	28.170732
Min length	3

Characters and Unicode

Total characters	1155
Distinct characters	42
Distinct categories	7 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	26 ?
Unique (%)	63.4%

Sample

1st row	Notepad++;Visual Studio
2nd row	Notepad++;Visual Studio;Visual Studio Code
3rd row	Rider;Visual Studio;Visual Studio Code
4th row	Visual Studio Code
5th row	Visual Studio Code;Webstorm

Common Values

Value	Count	Frequency (%)
Visual Studio Code	9	18.0%
Notepad++;Visual Studio;Visual Studio Code	2	4.0%
Visual Studio;Visual Studio Code	2	4.0%
IPython/Jupyter;PyCharm;Vim	2	4.0%
IntelliJ;PyCharm;Vim	1	2.0%
Atom;IntelliJ;Vim	1	2.0%
Nano;PyCharm	1	2.0%
IPython/Jupyter;Nano;PyCharm;Sublime Text	1	2.0%
IntelliJ;Vim	1	2.0%
IntelliJ;PhpStorm;PyCharm;RubyMine;Webstorm	1	2.0%
Other values (20)	20	40.0%
(Missing)	9	18.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
studio	29	26.1%
code	22	19.8%
visual	13	11.7%
studio;visual	5	4.5%
android	4	3.6%
notepad++;visual	3	2.7%
ipython/jupyter;pycharm;vim	2	1.8%
code;webstorm	2	1.8%
rider;visual	2	1.8%
vim;visual	2	1.8%
Other values (27)	27	24.3%

Most occurring characters

Value	Count	Frequency (%)
i	109	9.4%
o	91	7.9%
d	85	7.4%
u	83	7.2%
t	73	6.3%
	70	6.1%
e	66	5.7%
;	59	5.1%
l	58	5.0%
a	53	4.6%
Other values (32)	408	35.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	801	69.4%
Uppercase Letter	201	17.4%
Space Separator	70	6.1%
Other Punctuation	65	5.6%
Math Symbol	16	1.4%
Open Punctuation	1	0.1%
Close Punctuation	1	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
i	109	13.6%
o	91	11.4%
d	85	10.6%
u	83	10.4%
t	73	9.1%
e	66	8.2%
l	58	7.2%
a	53	6.6%
s	40	5.0%
m	31	3.9%
Other values (9)	112	14.0%

Uppercase Letter

Value	Count	Frequency (%)
V	45	22.4%
S	43	21.4%
C	34	16.9%
I	14	7.0%
J	14	7.0%
P	14	7.0%
N	11	5.5%
A	6	3.0%
R	5	2.5%
W	3	1.5%
Other values (6)	12	6.0%

Other Punctuation

Value	Count	Frequency (%)
;	59	90.8%
/	5	7.7%
,	1	1.5%

Space Separator

Value	Count	Frequency (%)
	70	100.0%

Math Symbol

Value	Count	Frequency (%)
+	16	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	1	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1002	86.8%
Common	153	13.2%

Most frequent character per script

Latin

Value	Count	Frequency (%)
i	109	10.9%
o	91	9.1%
d	85	8.5%
u	83	8.3%
t	73	7.3%
e	66	6.6%
l	58	5.8%
a	53	5.3%
V	45	4.5%
S	43	4.3%
Other values (25)	296	29.5%

Common

Value	Count	Frequency (%)
	70	45.8%
;	59	38.6%
+	16	10.5%
/	5	3.3%
(	1	0.7%
,	1	0.7%
)	1	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1155	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
i	109	9.4%
o	91	7.9%
d	85	7.4%
u	83	7.2%
t	73	6.3%
	70	6.1%
e	66	5.7%
;	59	5.1%
l	58	5.0%
a	53	4.6%
Other values (32)	408	35.3%

OpSysProfessional use
Categorical

HIGH CORRELATION MISSING

Distinct	9
Distinct (%)	20.5%
Missing	6
Missing (%)	12.0%
Memory size	528.0 B

Windows	14
macOS	10
Linux-based	8
Linux-based;macOS	3
Windows;Windows Subsystem for Linux (WSL)	3
Other values (4)	6

Length

Max length	41
Median length	33
Mean length	12.363636
Min length	5

Characters and Unicode

Total characters	544
Distinct characters	26
Distinct categories	7 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	4.5%

Sample

1st row	macOS
2nd row	Windows
3rd row	Windows
4th row	Windows
5th row	Linux-based;macOS

Common Values

Value	Count	Frequency (%)
Windows	14	28.0%
macOS	10	20.0%
Linux-based	8	16.0%
Linux-based;macOS	3	6.0%
Windows;Windows Subsystem for Linux (WSL)	3	6.0%
Linux-based;macOS;Windows	2	4.0%
Linux-based;Windows	2	4.0%
Windows Subsystem for Linux (WSL)	1	2.0%
macOS;Windows	1	2.0%
(Missing)	6	12.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
windows	15	25.0%
macos	10	16.7%
linux-based	8	13.3%
subsystem	4	6.7%
for	4	6.7%
linux	4	6.7%
wsl	4	6.7%
linux-based;macos	3	5.0%
windows;windows	3	5.0%
linux-based;macos;windows	2	3.3%
Other values (2)	3	5.0%

Most occurring characters

Value	Count	Frequency (%)
s	49	9.0%
n	45	8.3%
i	45	8.3%
d	41	7.5%
a	31	5.7%
W	30	5.5%
o	30	5.5%
w	26	4.8%
S	24	4.4%
L	23	4.2%
Other values (16)	200	36.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	399	73.3%
Uppercase Letter	93	17.1%
Space Separator	16	2.9%
Dash Punctuation	15	2.8%
Other Punctuation	13	2.4%
Open Punctuation	4	0.7%
Close Punctuation	4	0.7%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
s	49	12.3%
n	45	11.3%
i	45	11.3%
d	41	10.3%
a	31	7.8%
o	30	7.5%
w	26	6.5%
u	23	5.8%
m	20	5.0%
x	19	4.8%
Other values (7)	70	17.5%

Uppercase Letter

Value	Count	Frequency (%)
W	30	32.3%
S	24	25.8%
L	23	24.7%
O	16	17.2%

Space Separator

Value	Count	Frequency (%)
	16	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	15	100.0%

Other Punctuation

Value	Count	Frequency (%)
;	13	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	4	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	4	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	492	90.4%
Common	52	9.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
s	49	10.0%
n	45	9.1%
i	45	9.1%
d	41	8.3%
a	31	6.3%
W	30	6.1%
o	30	6.1%
w	26	5.3%
S	24	4.9%
L	23	4.7%
Other values (11)	148	30.1%

Common

Value	Count	Frequency (%)
	16	30.8%
-	15	28.8%
;	13	25.0%
(	4	7.7%
)	4	7.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	544	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
s	49	9.0%
n	45	8.3%
i	45	8.3%
d	41	7.5%
a	31	5.7%
W	30	5.5%
o	30	5.5%
w	26	4.8%
S	24	4.4%
L	23	4.2%
Other values (16)	200	36.8%

OpSysPersonal use
Categorical

HIGH CORRELATION MISSING

Distinct	10
Distinct (%)	20.8%
Missing	2
Missing (%)	4.0%
Memory size	528.0 B

Windows	18
macOS	9
Linux-based	9
macOS;Windows	3
Linux-based;Windows	3
Other values (5)	6

Length

Max length	53
Median length	41
Mean length	11.458333
Min length	5

Characters and Unicode

Total characters	550
Distinct characters	30
Distinct categories	7 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4 ?
Unique (%)	8.3%

Sample

1st row	Windows Subsystem for Linux (WSL)
2nd row	Windows
3rd row	Windows
4th row	macOS;Windows
5th row	macOS

Common Values

Value	Count	Frequency (%)
Windows	18	36.0%
macOS	9	18.0%
Linux-based	9	18.0%
macOS;Windows	3	6.0%
Linux-based;Windows	3	6.0%
Linux-based;macOS	2	4.0%
Windows Subsystem for Linux (WSL)	1	2.0%
Windows;Windows Subsystem for Linux (WSL)	1	2.0%
Other (please specify):	1	2.0%
Linux-based;Windows;Windows Subsystem for Linux (WSL)	1	2.0%
(Missing)	2	4.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
windows	19	30.6%
macos	9	14.5%
linux-based	9	14.5%
macos;windows	3	4.8%
linux-based;windows	3	4.8%
subsystem	3	4.8%
for	3	4.8%
linux	3	4.8%
wsl	3	4.8%
linux-based;macos	2	3.2%
Other values (5)	5	8.1%

Most occurring characters

Value	Count	Frequency (%)
s	52	9.5%
i	48	8.7%
n	47	8.5%
d	44	8.0%
W	32	5.8%
o	32	5.8%
a	30	5.5%
w	29	5.3%
e	22	4.0%
L	21	3.8%
Other values (20)	193	35.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	413	75.1%
Uppercase Letter	88	16.0%
Dash Punctuation	15	2.7%
Space Separator	14	2.5%
Other Punctuation	12	2.2%
Open Punctuation	4	0.7%
Close Punctuation	4	0.7%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
s	52	12.6%
i	48	11.6%
n	47	11.4%
d	44	10.7%
o	32	7.7%
a	30	7.3%
w	29	7.0%
e	22	5.3%
u	21	5.1%
b	18	4.4%
Other values (10)	70	16.9%

Uppercase Letter

Value	Count	Frequency (%)
W	32	36.4%
L	21	23.9%
S	20	22.7%
O	15	17.0%

Other Punctuation

Value	Count	Frequency (%)
;	11	91.7%
:	1	8.3%

Dash Punctuation

Value	Count	Frequency (%)
-	15	100.0%

Space Separator

Value	Count	Frequency (%)
	14	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	4	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	4	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	501	91.1%
Common	49	8.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
s	52	10.4%
i	48	9.6%
n	47	9.4%
d	44	8.8%
W	32	6.4%
o	32	6.4%
a	30	6.0%
w	29	5.8%
e	22	4.4%
L	21	4.2%
Other values (14)	144	28.7%

Common

Value	Count	Frequency (%)
-	15	30.6%
	14	28.6%
;	11	22.4%
(	4	8.2%
)	4	8.2%
:	1	2.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	550	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
s	52	9.5%
i	48	8.7%
n	47	8.5%
d	44	8.0%
W	32	5.8%
o	32	5.8%
a	30	5.5%
w	29	5.3%
e	22	4.0%
L	21	3.8%
Other values (20)	193	35.1%

VersionControlSystem
Categorical

HIGH CORRELATION IMBALANCE MISSING

Distinct	5
Distinct (%)	10.4%
Missing	2
Missing (%)	4.0%
Memory size	528.0 B

Git	43
I don't use one	2
Git;Other (please specify):	1
Mercurial;SVN	1
Git;SVN	1

Length

Max length	27
Median length	3
Mean length	4.2916667
Min length	3

Characters and Unicode

Total characters	206
Distinct characters	29
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	6.2%

Sample

1st row	Git
2nd row	Git
3rd row	Git
4th row	Git;Other (please specify):
5th row	Git

Common Values

Value	Count	Frequency (%)
Git	43	86.0%
I don't use one	2	4.0%
Git;Other (please specify):	1	2.0%
Mercurial;SVN	1	2.0%
Git;SVN	1	2.0%
(Missing)	2	4.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
git	43	76.8%
i	2	3.6%
don't	2	3.6%
use	2	3.6%
one	2	3.6%
git;other	1	1.8%
please	1	1.8%
specify	1	1.8%
mercurial;svn	1	1.8%
git;svn	1	1.8%

Most occurring characters

Value	Count	Frequency (%)
t	48	23.3%
i	47	22.8%
G	45	21.8%
e	9	4.4%
	8	3.9%
o	4	1.9%
n	4	1.9%
s	4	1.9%
;	3	1.5%
r	3	1.5%
Other values (19)	31	15.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	135	65.5%
Uppercase Letter	55	26.7%
Space Separator	8	3.9%
Other Punctuation	6	2.9%
Open Punctuation	1	0.5%
Close Punctuation	1	0.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
t	48	35.6%
i	47	34.8%
e	9	6.7%
o	4	3.0%
n	4	3.0%
s	4	3.0%
r	3	2.2%
u	3	2.2%
a	2	1.5%
c	2	1.5%
Other values (6)	9	6.7%

Uppercase Letter

Value	Count	Frequency (%)
G	45	81.8%
S	2	3.6%
V	2	3.6%
N	2	3.6%
I	2	3.6%
O	1	1.8%
M	1	1.8%

Other Punctuation

Value	Count	Frequency (%)
;	3	50.0%
'	2	33.3%
:	1	16.7%

Space Separator

Value	Count	Frequency (%)
	8	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	1	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	190	92.2%
Common	16	7.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
t	48	25.3%
i	47	24.7%
G	45	23.7%
e	9	4.7%
o	4	2.1%
n	4	2.1%
s	4	2.1%
r	3	1.6%
u	3	1.6%
a	2	1.1%
Other values (13)	21	11.1%

Common

Value	Count	Frequency (%)
	8	50.0%
;	3	18.8%
'	2	12.5%
(	1	6.2%
)	1	6.2%
:	1	6.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	206	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
t	48	23.3%
i	47	22.8%
G	45	21.8%
e	9	4.4%
	8	3.9%
o	4	1.9%
n	4	1.9%
s	4	1.9%
;	3	1.5%
r	3	1.5%
Other values (19)	31	15.0%

VCInteraction
Categorical

HIGH CORRELATION MISSING

Distinct	11
Distinct (%)	24.4%
Missing	5
Missing (%)	10.0%
Memory size	528.0 B

Code editor;Command-line	12
Command-line	11
Code editor	5
Code editor;Command-line;Version control hosting service web GUI;Dedicated version control GUI application	4
Command-line;Dedicated version control GUI application	3
Other values (6)	10

Length

Max length	106
Median length	94
Mean length	37.888889
Min length	11

Characters and Unicode

Total characters	1705
Distinct characters	27
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4 ?
Unique (%)	8.9%

Sample

1st row	Code editor
2nd row	Code editor;Command-line;Version control hosting service web GUI;Dedicated version control GUI application
3rd row	Code editor
4th row	Command-line;Version control hosting service web GUI;Dedicated version control GUI application
5th row	Code editor;Command-line

Common Values

Value	Count	Frequency (%)
Code editor;Command-line	12	24.0%
Command-line	11	22.0%
Code editor	5	10.0%
Code editor;Command-line;Version control hosting service web GUI;Dedicated version control GUI application	4	8.0%
Command-line;Dedicated version control GUI application	3	6.0%
Code editor;Dedicated version control GUI application	3	6.0%
Code editor;Command-line;Version control hosting service web GUI	3	6.0%
Command-line;Version control hosting service web GUI;Dedicated version control GUI application	1	2.0%
Version control hosting service web GUI;Dedicated version control GUI application	1	2.0%
Code editor;Command-line;Dedicated version control GUI application	1	2.0%
(Missing)	5	10.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
code	28	16.0%
control	23	13.1%
gui	17	9.7%
version	14	8.0%
application	13	7.4%
editor;command-line	12	6.9%
command-line	11	6.3%
web	10	5.7%
service	10	5.7%
hosting	10	5.7%
Other values (7)	27	15.4%

Most occurring characters

Value	Count	Frequency (%)
o	184	10.8%
e	171	10.0%
i	146	8.6%
n	141	8.3%
	130	7.6%
d	118	6.9%
t	87	5.1%
r	84	4.9%
a	75	4.4%
l	72	4.2%
Other values (17)	497	29.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1341	78.7%
Uppercase Letter	156	9.1%
Space Separator	130	7.6%
Other Punctuation	42	2.5%
Dash Punctuation	36	2.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	184	13.7%
e	171	12.8%
i	146	10.9%
n	141	10.5%
d	118	8.8%
t	87	6.5%
r	84	6.3%
a	75	5.6%
l	72	5.4%
m	72	5.4%
Other values (8)	191	14.2%

Uppercase Letter

Value	Count	Frequency (%)
C	64	41.0%
G	23	14.7%
U	23	14.7%
I	23	14.7%
D	13	8.3%
V	10	6.4%

Space Separator

Value	Count	Frequency (%)
	130	100.0%

Other Punctuation

Value	Count	Frequency (%)
;	42	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	36	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1497	87.8%
Common	208	12.2%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	184	12.3%
e	171	11.4%
i	146	9.8%
n	141	9.4%
d	118	7.9%
t	87	5.8%
r	84	5.6%
a	75	5.0%
l	72	4.8%
m	72	4.8%
Other values (14)	347	23.2%

Common

Value	Count	Frequency (%)
	130	62.5%
;	42	20.2%
-	36	17.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1705	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	184	10.8%
e	171	10.0%
i	146	8.6%
n	141	8.3%
	130	7.6%
d	118	6.9%
t	87	5.1%
r	84	4.9%
a	75	4.4%
l	72	4.2%
Other values (17)	497	29.1%

VCHostingPersonal use
Unsupported

MISSING REJECTED UNSUPPORTED

Missing	50
Missing (%)	100.0%
Memory size	528.0 B

VCHostingProfessional use
Unsupported

MISSING REJECTED UNSUPPORTED

Missing	50
Missing (%)	100.0%
Memory size	528.0 B

OfficeStackAsyncHaveWorkedWith
Categorical

HIGH CORRELATION MISSING

Distinct	15
Distinct (%)	57.7%
Missing	24
Missing (%)	48.0%
Memory size	528.0 B

Jira Work Management;Trello	4
Confluence	4
Confluence;Jira Work Management	4
Confluence;Jira Work Management;Notion;Trello	2
Jira Work Management	2
Other values (10)	10

Length

Max length	54
Median length	39.5
Mean length	24.846154
Min length	6

Characters and Unicode

Total characters	646
Distinct characters	30
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	10 ?
Unique (%)	38.5%

Sample

1st row	Jira Work Management;Trello
2nd row	Confluence
3rd row	Confluence;Jira Work Management
4th row	Confluence
5th row	Confluence;Jira Work Management;Notion;Trello

Common Values

Value	Count	Frequency (%)
Jira Work Management;Trello	4	8.0%
Confluence	4	8.0%
Confluence;Jira Work Management	4	8.0%
Confluence;Jira Work Management;Notion;Trello	2	4.0%
Jira Work Management	2	4.0%
Airtable;Confluence;Jira Work Management;Notion;Trello	1	2.0%
Asana;Jira Work Management;Trello	1	2.0%
Trello	1	2.0%
Notion	1	2.0%
Confluence;Notion	1	2.0%
Other values (5)	5	10.0%
(Missing)	24	48.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
work	17	28.3%
management;trello	7	11.7%
confluence;jira	7	11.7%
management	7	11.7%
jira	6	10.0%
confluence	4	6.7%
management;notion;trello	3	5.0%
asana;jira	2	3.3%
airtable;confluence;jira	1	1.7%
trello	1	1.7%
Other values (5)	5	8.3%

Most occurring characters

Value	Count	Frequency (%)
e	73	11.3%
n	70	10.8%
a	59	9.1%
o	56	8.7%
r	47	7.3%
l	39	6.0%
	34	5.3%
;	28	4.3%
i	25	3.9%
t	24	3.7%
Other values (20)	191	29.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	495	76.6%
Uppercase Letter	88	13.6%
Space Separator	34	5.3%
Other Punctuation	29	4.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	73	14.7%
n	70	14.1%
a	59	11.9%
o	56	11.3%
r	47	9.5%
l	39	7.9%
i	25	5.1%
t	24	4.8%
m	19	3.8%
k	18	3.6%
Other values (9)	65	13.1%

Uppercase Letter

Value	Count	Frequency (%)
J	17	19.3%
M	17	19.3%
W	17	19.3%
C	14	15.9%
T	12	13.6%
N	6	6.8%
A	4	4.5%
U	1	1.1%

Other Punctuation

Value	Count	Frequency (%)
;	28	96.6%
.	1	3.4%

Space Separator

Value	Count	Frequency (%)
	34	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	583	90.2%
Common	63	9.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	73	12.5%
n	70	12.0%
a	59	10.1%
o	56	9.6%
r	47	8.1%
l	39	6.7%
i	25	4.3%
t	24	4.1%
m	19	3.3%
k	18	3.1%
Other values (17)	153	26.2%

Common

Value	Count	Frequency (%)
	34	54.0%
;	28	44.4%
.	1	1.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	646	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	73	11.3%
n	70	10.8%
a	59	9.1%
o	56	8.7%
r	47	7.3%
l	39	6.0%
	34	5.3%
;	28	4.3%
i	25	3.9%
t	24	3.7%
Other values (20)	191	29.6%

OfficeStackAsyncWantToWorkWith
Categorical

HIGH CORRELATION MISSING

Distinct	10
Distinct (%)	55.6%
Missing	32
Missing (%)	64.0%
Memory size	528.0 B

Jira Work Management;Trello	3
Jira Work Management	3
Confluence;Jira Work Management	2
Notion	2
Trello	2
Other values (5)	6

Length

Max length	33
Median length	27
Mean length	17.111111
Min length	5

Characters and Unicode

Total characters	308
Distinct characters	27
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4 ?
Unique (%)	22.2%

Sample

1st row	Jira Work Management;Trello
2nd row	Confluence;Jira Work Management
3rd row	Notion;Trello
4th row	Jira Work Management;Trello
5th row	Notion

Common Values

Value	Count	Frequency (%)
Jira Work Management;Trello	3	6.0%
Jira Work Management	3	6.0%
Confluence;Jira Work Management	2	4.0%
Notion	2	4.0%
Trello	2	4.0%
Confluence	2	4.0%
Notion;Trello	1	2.0%
Asana;Jira Work Management;Trello	1	2.0%
Asana	1	2.0%
monday.com	1	2.0%
(Missing)	32	64.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
work	9	25.0%
jira	6	16.7%
management	5	13.9%
management;trello	4	11.1%
confluence;jira	2	5.6%
notion	2	5.6%
trello	2	5.6%
confluence	2	5.6%
notion;trello	1	2.8%
asana;jira	1	2.8%
Other values (2)	2	5.6%

Most occurring characters

Value	Count	Frequency (%)
e	33	10.7%
a	32	10.4%
n	32	10.4%
o	28	9.1%
r	25	8.1%
	18	5.8%
l	18	5.8%
t	12	3.9%
i	12	3.9%
m	11	3.6%
Other values (17)	87	28.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	238	77.3%
Uppercase Letter	43	14.0%
Space Separator	18	5.8%
Other Punctuation	9	2.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	33	13.9%
a	32	13.4%
n	32	13.4%
o	28	11.8%
r	25	10.5%
l	18	7.6%
t	12	5.0%
i	12	5.0%
m	11	4.6%
g	9	3.8%
Other values (7)	26	10.9%

Uppercase Letter

Value	Count	Frequency (%)
J	9	20.9%
M	9	20.9%
W	9	20.9%
T	7	16.3%
C	4	9.3%
N	3	7.0%
A	2	4.7%

Other Punctuation

Value	Count	Frequency (%)
;	8	88.9%
.	1	11.1%

Space Separator

Value	Count	Frequency (%)
	18	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	281	91.2%
Common	27	8.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	33	11.7%
a	32	11.4%
n	32	11.4%
o	28	10.0%
r	25	8.9%
l	18	6.4%
t	12	4.3%
i	12	4.3%
m	11	3.9%
J	9	3.2%
Other values (14)	69	24.6%

Common

Value	Count	Frequency (%)
	18	66.7%
;	8	29.6%
.	1	3.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	308	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	33	10.7%
a	32	10.4%
n	32	10.4%
o	28	9.1%
r	25	8.1%
	18	5.8%
l	18	5.8%
t	12	3.9%
i	12	3.9%
m	11	3.6%
Other values (17)	87	28.2%

OfficeStackSyncHaveWorkedWith
Categorical

HIGH CORRELATION MISSING

Distinct	14
Distinct (%)	35.9%
Missing	11
Missing (%)	22.0%
Memory size	528.0 B

Microsoft Teams	8
Microsoft Teams;Slack;Zoom	7
Microsoft Teams;Zoom	5
Slack;Zoom	4
Microsoft Teams;Slack	3
Other values (9)	12

Length

Max length	68
Median length	33
Mean length	20.769231
Min length	4

Characters and Unicode

Total characters	810
Distinct characters	27
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	6 ?
Unique (%)	15.4%

Sample

1st row	Microsoft Teams
2nd row	Slack;Zoom
3rd row	Microsoft Teams;Zoom
4th row	Rocketchat;Slack;Zoom
5th row	Google Chat;Microsoft Teams;Slack;Zoom

Common Values

Value	Count	Frequency (%)
Microsoft Teams	8	16.0%
Microsoft Teams;Slack;Zoom	7	14.0%
Microsoft Teams;Zoom	5	10.0%
Slack;Zoom	4	8.0%
Microsoft Teams;Slack	3	6.0%
Google Chat;Microsoft Teams;Slack;Zoom	2	4.0%
Google Chat;Slack;Zoom	2	4.0%
Slack	2	4.0%
Rocketchat;Slack;Zoom	1	2.0%
Google Chat;Microsoft Teams;Zoom	1	2.0%
Other values (4)	4	8.0%
(Missing)	11	22.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
microsoft	23	29.9%
teams;slack;zoom	9	11.7%
teams	8	10.4%
google	7	9.1%
teams;zoom	6	7.8%
chat;microsoft	5	6.5%
slack;zoom	4	5.2%
teams;slack	4	5.2%
slack	2	2.6%
chat;slack;zoom	2	2.6%
Other values (7)	7	9.1%

Most occurring characters

Value	Count	Frequency (%)
o	122	15.1%
a	63	7.8%
s	58	7.2%
c	55	6.8%
m	53	6.5%
;	48	5.9%
e	41	5.1%
t	39	4.8%
	38	4.7%
l	33	4.1%
Other values (17)	260	32.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	598	73.8%
Uppercase Letter	126	15.6%
Other Punctuation	48	5.9%
Space Separator	38	4.7%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	122	20.4%
a	63	10.5%
s	58	9.7%
c	55	9.2%
m	53	8.9%
e	41	6.9%
t	39	6.5%
l	33	5.5%
i	30	5.0%
r	29	4.8%
Other values (7)	75	12.5%

Uppercase Letter

Value	Count	Frequency (%)
T	29	23.0%
M	28	22.2%
S	24	19.0%
Z	24	19.0%
C	10	7.9%
G	8	6.3%
R	2	1.6%
W	1	0.8%

Other Punctuation

Value	Count	Frequency (%)
;	48	100.0%

Space Separator

Value	Count	Frequency (%)
	38	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	724	89.4%
Common	86	10.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	122	16.9%
a	63	8.7%
s	58	8.0%
c	55	7.6%
m	53	7.3%
e	41	5.7%
t	39	5.4%
l	33	4.6%
i	30	4.1%
r	29	4.0%
Other values (15)	201	27.8%

Common

Value	Count	Frequency (%)
;	48	55.8%
	38	44.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	810	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	122	15.1%
a	63	7.8%
s	58	7.2%
c	55	6.8%
m	53	6.5%
;	48	5.9%
e	41	5.1%
t	39	4.8%
	38	4.7%
l	33	4.1%
Other values (17)	260	32.1%

OfficeStackSyncWantToWorkWith
Categorical

HIGH CORRELATION MISSING

Distinct	10
Distinct (%)	32.3%
Missing	19
Missing (%)	38.0%
Memory size	528.0 B

Microsoft Teams	7
Slack	7
Slack;Zoom	5
Microsoft Teams;Slack	3
Microsoft Teams;Zoom	3
Other values (5)	6

Length

Max length	22
Median length	20
Mean length	13.258065
Min length	4

Characters and Unicode

Total characters	411
Distinct characters	24
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4 ?
Unique (%)	12.9%

Sample

1st row	Microsoft Teams
2nd row	Slack;Zoom
3rd row	Rocketchat;Slack;Zoom
4th row	Google Chat;Slack;Zoom
5th row	Microsoft Teams

Common Values

Value	Count	Frequency (%)
Microsoft Teams	7	14.0%
Slack	7	14.0%
Slack;Zoom	5	10.0%
Microsoft Teams;Slack	3	6.0%
Microsoft Teams;Zoom	3	6.0%
Google Chat;Slack	2	4.0%
Rocketchat;Slack;Zoom	1	2.0%
Google Chat;Slack;Zoom	1	2.0%
Zoom	1	2.0%
RingCentral;Slack	1	2.0%
(Missing)	19	38.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
microsoft	13	27.7%
teams	7	14.9%
slack	7	14.9%
slack;zoom	5	10.6%
teams;slack	3	6.4%
teams;zoom	3	6.4%
google	3	6.4%
chat;slack	2	4.3%
rocketchat;slack;zoom	1	2.1%
chat;slack;zoom	1	2.1%
Other values (2)	2	4.3%

Most occurring characters

Value	Count	Frequency (%)
o	55	13.4%
a	38	9.2%
c	35	8.5%
s	26	6.3%
m	24	5.8%
l	24	5.8%
k	21	5.1%
S	20	4.9%
t	19	4.6%
;	18	4.4%
Other values (14)	131	31.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	311	75.7%
Uppercase Letter	66	16.1%
Other Punctuation	18	4.4%
Space Separator	16	3.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	55	17.7%
a	38	12.2%
c	35	11.3%
s	26	8.4%
m	24	7.7%
l	24	7.7%
k	21	6.8%
t	19	6.1%
e	18	5.8%
r	14	4.5%
Other values (5)	37	11.9%

Uppercase Letter

Value	Count	Frequency (%)
S	20	30.3%
M	13	19.7%
T	13	19.7%
Z	11	16.7%
C	4	6.1%
G	3	4.5%
R	2	3.0%

Other Punctuation

Value	Count	Frequency (%)
;	18	100.0%

Space Separator

Value	Count	Frequency (%)
	16	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	377	91.7%
Common	34	8.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	55	14.6%
a	38	10.1%
c	35	9.3%
s	26	6.9%
m	24	6.4%
l	24	6.4%
k	21	5.6%
S	20	5.3%
t	19	5.0%
e	18	4.8%
Other values (12)	97	25.7%

Common

Value	Count	Frequency (%)
;	18	52.9%
	16	47.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	411	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	55	13.4%
a	38	9.2%
c	35	8.5%
s	26	6.3%
m	24	5.8%
l	24	5.8%
k	21	5.1%
S	20	4.9%
t	19	4.6%
;	18	4.4%
Other values (14)	131	31.9%

Blockchain
Categorical

HIGH CORRELATION MISSING

Distinct	6
Distinct (%)	12.8%
Missing	3
Missing (%)	6.0%
Memory size	528.0 B

Very unfavorable	16
Indifferent	10
Unfavorable	7
Favorable	5
Unsure	5

Length

Max length	16
Median length	14
Mean length	12.212766
Min length	6

Characters and Unicode

Total characters	574
Distinct characters	20
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Very unfavorable
2nd row	Very unfavorable
3rd row	Very unfavorable
4th row	Unfavorable
5th row	Very unfavorable

Common Values

Value	Count	Frequency (%)
Very unfavorable	16	32.0%
Indifferent	10	20.0%
Unfavorable	7	14.0%
Favorable	5	10.0%
Unsure	5	10.0%
Very favorable	4	8.0%
(Missing)	3	6.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
unfavorable	23	34.3%
very	20	29.9%
indifferent	10	14.9%
favorable	9	13.4%
unsure	5	7.5%

Most occurring characters

Value	Count	Frequency (%)
e	77	13.4%
r	67	11.7%
a	64	11.1%
n	48	8.4%
f	47	8.2%
o	32	5.6%
l	32	5.6%
b	32	5.6%
v	32	5.6%
u	21	3.7%
Other values (10)	122	21.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	507	88.3%
Uppercase Letter	47	8.2%
Space Separator	20	3.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	77	15.2%
r	67	13.2%
a	64	12.6%
n	48	9.5%
f	47	9.3%
o	32	6.3%
l	32	6.3%
b	32	6.3%
v	32	6.3%
u	21	4.1%
Other values (5)	55	10.8%

Uppercase Letter

Value	Count	Frequency (%)
V	20	42.6%
U	12	25.5%
I	10	21.3%
F	5	10.6%

Space Separator

Value	Count	Frequency (%)
	20	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	554	96.5%
Common	20	3.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	77	13.9%
r	67	12.1%
a	64	11.6%
n	48	8.7%
f	47	8.5%
o	32	5.8%
l	32	5.8%
b	32	5.8%
v	32	5.8%
u	21	3.8%
Other values (9)	102	18.4%

Common

Value	Count	Frequency (%)
	20	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	574	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	77	13.4%
r	67	11.7%
a	64	11.1%
n	48	8.4%
f	47	8.2%
o	32	5.6%
l	32	5.6%
b	32	5.6%
v	32	5.6%
u	21	3.7%
Other values (10)	122	21.3%

NEWSOSites
Categorical

HIGH CORRELATION MISSING

Distinct	5
Distinct (%)	10.4%
Missing	2
Missing (%)	4.0%
Memory size	528.0 B

Stack Overflow;Stack Exchange	29
Stack Overflow	7
Collectives on Stack Overflow;Stack Overflow for Teams (private knowledge sharing & collaboration platform for companies);Stack Overflow;Stack Exchange	5
Collectives on Stack Overflow;Stack Overflow;Stack Exchange	5
Stack Overflow for Teams (private knowledge sharing & collaboration platform for companies);Stack Overflow;Stack Exchange	2

Length

Max length	151
Median length	29
Mean length	46.479167
Min length	14

Characters and Unicode

Total characters	2231
Distinct characters	31
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Collectives on Stack Overflow;Stack Overflow for Teams (private knowledge sharing & collaboration platform for companies);Stack Overflow;Stack Exchange
2nd row	Collectives on Stack Overflow;Stack Overflow;Stack Exchange
3rd row	Collectives on Stack Overflow;Stack Overflow for Teams (private knowledge sharing & collaboration platform for companies);Stack Overflow;Stack Exchange
4th row	Collectives on Stack Overflow;Stack Overflow for Teams (private knowledge sharing & collaboration platform for companies);Stack Overflow;Stack Exchange
5th row	Stack Overflow;Stack Exchange

Common Values

Value	Count	Frequency (%)
Stack Overflow;Stack Exchange	29	58.0%
Stack Overflow	7	14.0%
Collectives on Stack Overflow;Stack Overflow for Teams (private knowledge sharing & collaboration platform for companies);Stack Overflow;Stack Exchange	5	10.0%
Collectives on Stack Overflow;Stack Overflow;Stack Exchange	5	10.0%
Stack Overflow for Teams (private knowledge sharing & collaboration platform for companies);Stack Overflow;Stack Exchange	2	4.0%
(Missing)	2	4.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
overflow;stack	51	20.9%
stack	48	19.7%
exchange	41	16.8%
overflow	14	5.7%
for	14	5.7%
collectives	10	4.1%
on	10	4.1%
teams	7	2.9%
private	7	2.9%
knowledge	7	2.9%
Other values (5)	35	14.3%

Most occurring characters

Value	Count	Frequency (%)
a	196	8.8%
	196	8.8%
c	171	7.7%
e	161	7.2%
o	141	6.3%
t	137	6.1%
l	113	5.1%
k	113	5.1%
r	107	4.8%
S	106	4.8%
Other values (21)	790	35.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1727	77.4%
Uppercase Letter	229	10.3%
Space Separator	196	8.8%
Other Punctuation	65	2.9%
Open Punctuation	7	0.3%
Close Punctuation	7	0.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	196	11.3%
c	171	9.9%
e	161	9.3%
o	141	8.2%
t	137	7.9%
l	113	6.5%
k	113	6.5%
r	107	6.2%
f	86	5.0%
v	82	4.7%
Other values (11)	420	24.3%

Uppercase Letter

Value	Count	Frequency (%)
S	106	46.3%
O	65	28.4%
E	41	17.9%
C	10	4.4%
T	7	3.1%

Other Punctuation

Value	Count	Frequency (%)
;	58	89.2%
&	7	10.8%

Space Separator

Value	Count	Frequency (%)
	196	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	7	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	7	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1956	87.7%
Common	275	12.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	196	10.0%
c	171	8.7%
e	161	8.2%
o	141	7.2%
t	137	7.0%
l	113	5.8%
k	113	5.8%
r	107	5.5%
S	106	5.4%
f	86	4.4%
Other values (16)	625	32.0%

Common

Value	Count	Frequency (%)
	196	71.3%
;	58	21.1%
(	7	2.5%
&	7	2.5%
)	7	2.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2231	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	196	8.8%
	196	8.8%
c	171	7.7%
e	161	7.2%
o	141	6.3%
t	137	6.1%
l	113	5.1%
k	113	5.1%
r	107	4.8%
S	106	4.8%
Other values (21)	790	35.4%

SOVisitFreq
Categorical

Distinct	5
Distinct (%)	10.4%
Missing	2
Missing (%)	4.0%
Memory size	528.0 B

Daily or almost daily	19
Multiple times per day	17
A few times per month or weekly	7
A few times per week	4
Less than once per month or monthly	1

Length

Max length	35
Median length	31
Mean length	23.020833
Min length	20

Characters and Unicode

Total characters	1105
Distinct characters	24
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	2.1%

Sample

1st row	Daily or almost daily
2nd row	Multiple times per day
3rd row	Daily or almost daily
4th row	Multiple times per day
5th row	Multiple times per day

Common Values

Value	Count	Frequency (%)
Daily or almost daily	19	38.0%
Multiple times per day	17	34.0%
A few times per month or weekly	7	14.0%
A few times per week	4	8.0%
Less than once per month or monthly	1	2.0%
(Missing)	2	4.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
daily	38	17.3%
per	29	13.2%
times	28	12.7%
or	27	12.3%
almost	19	8.6%
multiple	17	7.7%
day	17	7.7%
a	11	5.0%
few	11	5.0%
month	8	3.6%
Other values (6)	15	6.8%

Most occurring characters

Value	Count	Frequency (%)
	172	15.6%
e	109	9.9%
l	99	9.0%
i	83	7.5%
a	75	6.8%
t	74	6.7%
y	63	5.7%
o	56	5.1%
r	56	5.1%
m	56	5.1%
Other values (14)	262	23.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	885	80.1%
Space Separator	172	15.6%
Uppercase Letter	48	4.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	109	12.3%
l	99	11.2%
i	83	9.4%
a	75	8.5%
t	74	8.4%
y	63	7.1%
o	56	6.3%
r	56	6.3%
m	56	6.3%
s	49	5.5%
Other values (9)	165	18.6%

Uppercase Letter

Value	Count	Frequency (%)
D	19	39.6%
M	17	35.4%
A	11	22.9%
L	1	2.1%

Space Separator

Value	Count	Frequency (%)
	172	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	933	84.4%
Common	172	15.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	109	11.7%
l	99	10.6%
i	83	8.9%
a	75	8.0%
t	74	7.9%
y	63	6.8%
o	56	6.0%
r	56	6.0%
m	56	6.0%
s	49	5.3%
Other values (13)	213	22.8%

Common

Value	Count	Frequency (%)
	172	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1105	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	172	15.6%
e	109	9.9%
l	99	9.0%
i	83	7.5%
a	75	6.8%
t	74	6.7%
y	63	5.7%
o	56	5.1%
r	56	5.1%
m	56	5.1%
Other values (14)	262	23.7%

SOAccount
Categorical

HIGH CORRELATION MISSING

Distinct	3
Distinct (%)	6.2%
Missing	2
Missing (%)	4.0%
Memory size	528.0 B

Yes	40
No	5
Not sure/can't remember	3

Length

Max length	23
Median length	3
Mean length	4.1458333
Min length	2

Characters and Unicode

Total characters	199
Distinct characters	16
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Yes
2nd row	Yes
3rd row	Yes
4th row	Yes
5th row	Yes

Common Values

Value	Count	Frequency (%)
Yes	40	80.0%
No	5	10.0%
Not sure/can't remember	3	6.0%
(Missing)	2	4.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
yes	40	74.1%
no	5	9.3%
not	3	5.6%
sure/can't	3	5.6%
remember	3	5.6%

Most occurring characters

Value	Count	Frequency (%)
e	52	26.1%
s	43	21.6%
Y	40	20.1%
r	9	4.5%
N	8	4.0%
o	8	4.0%
t	6	3.0%
	6	3.0%
m	6	3.0%
u	3	1.5%
Other values (6)	18	9.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	139	69.8%
Uppercase Letter	48	24.1%
Space Separator	6	3.0%
Other Punctuation	6	3.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	52	37.4%
s	43	30.9%
r	9	6.5%
o	8	5.8%
t	6	4.3%
m	6	4.3%
u	3	2.2%
c	3	2.2%
a	3	2.2%
n	3	2.2%

Uppercase Letter

Value	Count	Frequency (%)
Y	40	83.3%
N	8	16.7%

Other Punctuation

Value	Count	Frequency (%)
/	3	50.0%
'	3	50.0%

Space Separator

Value	Count	Frequency (%)
	6	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	187	94.0%
Common	12	6.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	52	27.8%
s	43	23.0%
Y	40	21.4%
r	9	4.8%
N	8	4.3%
o	8	4.3%
t	6	3.2%
m	6	3.2%
u	3	1.6%
c	3	1.6%
Other values (3)	9	4.8%

Common

Value	Count	Frequency (%)
	6	50.0%
/	3	25.0%
'	3	25.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	199	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	52	26.1%
s	43	21.6%
Y	40	20.1%
r	9	4.5%
N	8	4.0%
o	8	4.0%
t	6	3.0%
	6	3.0%
m	6	3.0%
u	3	1.5%
Other values (6)	18	9.0%

SOPartFreq
Categorical

HIGH CORRELATION MISSING

Distinct	6
Distinct (%)	15.0%
Missing	10
Missing (%)	20.0%
Memory size	528.0 B

Less than once per month or monthly	11
Multiple times per day	7
I have never participated in Q&A on Stack Overflow	7
A few times per month or weekly	7
Daily or almost daily	5

Length

Max length	50
Median length	31
Mean length	31.775
Min length	20

Characters and Unicode

Total characters	1271
Distinct characters	30
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Daily or almost daily
2nd row	Multiple times per day
3rd row	A few times per week
4th row	Daily or almost daily
5th row	Multiple times per day

Common Values

Value	Count	Frequency (%)
Less than once per month or monthly	11	22.0%
Multiple times per day	7	14.0%
I have never participated in Q&A on Stack Overflow	7	14.0%
A few times per month or weekly	7	14.0%
Daily or almost daily	5	10.0%
A few times per week	3	6.0%
(Missing)	10	20.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
per	28	11.1%
or	23	9.1%
month	18	7.1%
times	17	6.7%
less	11	4.4%
once	11	4.4%
monthly	11	4.4%
than	11	4.4%
daily	10	4.0%
few	10	4.0%
Other values (15)	102	40.5%

Most occurring characters

Value	Count	Frequency (%)
	212	16.7%
e	139	10.9%
t	90	7.1%
o	82	6.5%
n	72	5.7%
r	72	5.7%
a	61	4.8%
i	55	4.3%
l	54	4.2%
m	51	4.0%
Other values (20)	383	30.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	984	77.4%
Space Separator	212	16.7%
Uppercase Letter	68	5.4%
Other Punctuation	7	0.6%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	139	14.1%
t	90	9.1%
o	82	8.3%
n	72	7.3%
r	72	7.3%
a	61	6.2%
i	55	5.6%
l	54	5.5%
m	51	5.2%
p	49	5.0%
Other values (10)	259	26.3%

Uppercase Letter

Value	Count	Frequency (%)
A	17	25.0%
L	11	16.2%
O	7	10.3%
S	7	10.3%
M	7	10.3%
Q	7	10.3%
I	7	10.3%
D	5	7.4%

Space Separator

Value	Count	Frequency (%)
	212	100.0%

Other Punctuation

Value	Count	Frequency (%)
&	7	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1052	82.8%
Common	219	17.2%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	139	13.2%
t	90	8.6%
o	82	7.8%
n	72	6.8%
r	72	6.8%
a	61	5.8%
i	55	5.2%
l	54	5.1%
m	51	4.8%
p	49	4.7%
Other values (18)	327	31.1%

Common

Value	Count	Frequency (%)
	212	96.8%
&	7	3.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1271	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	212	16.7%
e	139	10.9%
t	90	7.1%
o	82	6.5%
n	72	5.7%
r	72	5.7%
a	61	4.8%
i	55	4.3%
l	54	4.2%
m	51	4.0%
Other values (20)	383	30.1%

SOComm
Categorical

HIGH CORRELATION MISSING

Distinct	6
Distinct (%)	12.5%
Missing	2
Missing (%)	4.0%
Memory size	528.0 B

Yes, definitely	15
No, not really	12
Neutral	8
Yes, somewhat	8
No, not at all	4

Length

Max length	15
Median length	14
Mean length	12.854167
Min length	7

Characters and Unicode

Total characters	617
Distinct characters	20
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	2.1%

Sample

1st row	Not sure
2nd row	Neutral
3rd row	Yes, definitely
4th row	Yes, definitely
5th row	Yes, definitely

Common Values

Value	Count	Frequency (%)
Yes, definitely	15	30.0%
No, not really	12	24.0%
Neutral	8	16.0%
Yes, somewhat	8	16.0%
No, not at all	4	8.0%
Not sure	1	2.0%
(Missing)	2	4.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
yes	23	21.3%
not	17	15.7%
no	16	14.8%
definitely	15	13.9%
really	12	11.1%
neutral	8	7.4%
somewhat	8	7.4%
at	4	3.7%
all	4	3.7%
sure	1	0.9%

Most occurring characters

Value	Count	Frequency (%)
e	82	13.3%
	60	9.7%
l	55	8.9%
t	52	8.4%
o	41	6.6%
,	39	6.3%
a	36	5.8%
s	32	5.2%
n	31	5.0%
i	30	4.9%
Other values (10)	159	25.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	470	76.2%
Space Separator	60	9.7%
Uppercase Letter	48	7.8%
Other Punctuation	39	6.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	82	17.4%
l	55	11.7%
t	52	11.1%
o	41	8.7%
a	36	7.7%
s	32	6.8%
n	31	6.6%
i	30	6.4%
y	27	5.7%
r	21	4.5%
Other values (6)	63	13.4%

Uppercase Letter

Value	Count	Frequency (%)
N	25	52.1%
Y	23	47.9%

Space Separator

Value	Count	Frequency (%)
	60	100.0%

Other Punctuation

Value	Count	Frequency (%)
,	39	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	518	84.0%
Common	99	16.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	82	15.8%
l	55	10.6%
t	52	10.0%
o	41	7.9%
a	36	6.9%
s	32	6.2%
n	31	6.0%
i	30	5.8%
y	27	5.2%
N	25	4.8%
Other values (8)	107	20.7%

Common

Value	Count	Frequency (%)
	60	60.6%
,	39	39.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	617	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	82	13.3%
	60	9.7%
l	55	8.9%
t	52	8.4%
o	41	6.6%
,	39	6.3%
a	36	5.8%
s	32	5.2%
n	31	5.0%
i	30	4.9%
Other values (10)	159	25.8%

Age
Categorical

HIGH CORRELATION MISSING

Distinct	6
Distinct (%)	13.0%
Missing	4
Missing (%)	8.0%
Memory size	528.0 B

25-34 years old	21
35-44 years old	9
18-24 years old	8
45-54 years old	3
55-64 years old	3

Length

Max length	18
Median length	15
Mean length	15.130435
Min length	15

Characters and Unicode

Total characters	696
Distinct characters	19
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	25-34 years old
2nd row	35-44 years old
3rd row	25-34 years old
4th row	25-34 years old
5th row	Under 18 years old

Common Values

Value	Count	Frequency (%)
25-34 years old	21	42.0%
35-44 years old	9	18.0%
18-24 years old	8	16.0%
45-54 years old	3	6.0%
55-64 years old	3	6.0%
Under 18 years old	2	4.0%
(Missing)	4	8.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
years	46	32.9%
old	46	32.9%
25-34	21	15.0%
35-44	9	6.4%
18-24	8	5.7%
45-54	3	2.1%
55-64	3	2.1%
under	2	1.4%
18	2	1.4%

Most occurring characters

Value	Count	Frequency (%)
	94	13.5%
4	56	8.0%
r	48	6.9%
d	48	6.9%
e	48	6.9%
y	46	6.6%
a	46	6.6%
s	46	6.6%
o	46	6.6%
l	46	6.6%
Other values (9)	172	24.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	376	54.0%
Decimal Number	180	25.9%
Space Separator	94	13.5%
Dash Punctuation	44	6.3%
Uppercase Letter	2	0.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
r	48	12.8%
d	48	12.8%
e	48	12.8%
y	46	12.2%
a	46	12.2%
s	46	12.2%
o	46	12.2%
l	46	12.2%
n	2	0.5%

Decimal Number

Value	Count	Frequency (%)
4	56	31.1%
5	42	23.3%
3	30	16.7%
2	29	16.1%
1	10	5.6%
8	10	5.6%
6	3	1.7%

Space Separator

Value	Count	Frequency (%)
	94	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	44	100.0%

Uppercase Letter

Value	Count	Frequency (%)
U	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	378	54.3%
Common	318	45.7%

Most frequent character per script

Latin

Value	Count	Frequency (%)
r	48	12.7%
d	48	12.7%
e	48	12.7%
y	46	12.2%
a	46	12.2%
s	46	12.2%
o	46	12.2%
l	46	12.2%
U	2	0.5%
n	2	0.5%

Common

Value	Count	Frequency (%)
	94	29.6%
4	56	17.6%
-	44	13.8%
5	42	13.2%
3	30	9.4%
2	29	9.1%
1	10	3.1%
8	10	3.1%
6	3	0.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	696	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	94	13.5%
4	56	8.0%
r	48	6.9%
d	48	6.9%
e	48	6.9%
y	46	6.6%
a	46	6.6%
s	46	6.6%
o	46	6.6%
l	46	6.6%
Other values (9)	172	24.7%

Gender
Categorical

HIGH CORRELATION IMBALANCE MISSING

Distinct	5
Distinct (%)	10.9%
Missing	4
Missing (%)	8.0%
Memory size	528.0 B

Man	37
Woman	6
Or, in your own words:	1
Non-binary, genderqueer, or gender non-conforming	1
Prefer not to say	1

Length

Max length	49
Median length	3
Mean length	4.9782609
Min length	3

Characters and Unicode

Total characters	229
Distinct characters	27
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	6.5%

Sample

1st row	Man
2nd row	Man
3rd row	Or, in your own words:
4th row	Man
5th row	Man

Common Values

Value	Count	Frequency (%)
Man	37	74.0%
Woman	6	12.0%
Or, in your own words:	1	2.0%
Non-binary, genderqueer, or gender non-conforming	1	2.0%
Prefer not to say	1	2.0%
(Missing)	4	8.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
man	37	64.9%
woman	6	10.5%
or	2	3.5%
in	1	1.8%
your	1	1.8%
own	1	1.8%
words	1	1.8%
non-binary	1	1.8%
genderqueer	1	1.8%
gender	1	1.8%
Other values (5)	5	8.8%

Most occurring characters

Value	Count	Frequency (%)
n	54	23.6%
a	45	19.7%
M	37	16.2%
o	16	7.0%
r	11	4.8%
	11	4.8%
e	8	3.5%
m	7	3.1%
W	6	2.6%
,	3	1.3%
Other values (17)	31	13.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	166	72.5%
Uppercase Letter	46	20.1%
Space Separator	11	4.8%
Other Punctuation	4	1.7%
Dash Punctuation	2	0.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	54	32.5%
a	45	27.1%
o	16	9.6%
r	11	6.6%
e	8	4.8%
m	7	4.2%
i	3	1.8%
y	3	1.8%
d	3	1.8%
g	3	1.8%
Other values (8)	13	7.8%

Uppercase Letter

Value	Count	Frequency (%)
M	37	80.4%
W	6	13.0%
N	1	2.2%
O	1	2.2%
P	1	2.2%

Other Punctuation

Value	Count	Frequency (%)
,	3	75.0%
:	1	25.0%

Space Separator

Value	Count	Frequency (%)
	11	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	212	92.6%
Common	17	7.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	54	25.5%
a	45	21.2%
M	37	17.5%
o	16	7.5%
r	11	5.2%
e	8	3.8%
m	7	3.3%
W	6	2.8%
i	3	1.4%
y	3	1.4%
Other values (13)	22	10.4%

Common

Value	Count	Frequency (%)
	11	64.7%
,	3	17.6%
-	2	11.8%
:	1	5.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	229	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	54	23.6%
a	45	19.7%
M	37	16.2%
o	16	7.0%
r	11	4.8%
	11	4.8%
e	8	3.5%
m	7	3.1%
W	6	2.6%
,	3	1.3%
Other values (17)	31	13.5%

Trans
Categorical

HIGH CORRELATION IMBALANCE MISSING

Distinct	3
Distinct (%)	6.5%
Missing	4
Missing (%)	8.0%
Memory size	528.0 B

No	43
Yes	2
Or, in your own words:	1

Length

Max length	22
Median length	2
Mean length	2.4782609
Min length	2

Characters and Unicode

Total characters	114
Distinct characters	16
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	2.2%

Sample

1st row	No
2nd row	No
3rd row	Or, in your own words:
4th row	No
5th row	No

Common Values

Value	Count	Frequency (%)
No	43	86.0%
Yes	2	4.0%
Or, in your own words:	1	2.0%
(Missing)	4	8.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
no	43	86.0%
yes	2	4.0%
or	1	2.0%
in	1	2.0%
your	1	2.0%
own	1	2.0%
words	1	2.0%

Most occurring characters

Value	Count	Frequency (%)
o	46	40.4%
N	43	37.7%
	4	3.5%
s	3	2.6%
r	3	2.6%
Y	2	1.8%
e	2	1.8%
n	2	1.8%
w	2	1.8%
O	1	0.9%
Other values (6)	6	5.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	62	54.4%
Uppercase Letter	46	40.4%
Space Separator	4	3.5%
Other Punctuation	2	1.8%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	46	74.2%
s	3	4.8%
r	3	4.8%
e	2	3.2%
n	2	3.2%
w	2	3.2%
i	1	1.6%
y	1	1.6%
u	1	1.6%
d	1	1.6%

Uppercase Letter

Value	Count	Frequency (%)
N	43	93.5%
Y	2	4.3%
O	1	2.2%

Other Punctuation

Value	Count	Frequency (%)
,	1	50.0%
:	1	50.0%

Space Separator

Value	Count	Frequency (%)
	4	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	108	94.7%
Common	6	5.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	46	42.6%
N	43	39.8%
s	3	2.8%
r	3	2.8%
Y	2	1.9%
e	2	1.9%
n	2	1.9%
w	2	1.9%
O	1	0.9%
i	1	0.9%
Other values (3)	3	2.8%

Common

Value	Count	Frequency (%)
	4	66.7%
,	1	16.7%
:	1	16.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	114	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	46	40.4%
N	43	37.7%
	4	3.5%
s	3	2.6%
r	3	2.6%
Y	2	1.8%
e	2	1.8%
n	2	1.8%
w	2	1.8%
O	1	0.9%
Other values (6)	6	5.3%

Sexuality
Categorical

HIGH CORRELATION MISSING

Distinct	7
Distinct (%)	15.9%
Missing	6
Missing (%)	12.0%
Memory size	528.0 B

Straight / Heterosexual	32
Bisexual	4
Prefer to self-describe:	3
Bisexual;Straight / Heterosexual	2
Gay or Lesbian	1
Other values (2)	2

Length

Max length	32
Median length	23
Mean length	21.931818
Min length	8

Characters and Unicode

Total characters	965
Distinct characters	30
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	6.8%

Sample

1st row	Bisexual
2nd row	Straight / Heterosexual
3rd row	Prefer to self-describe:
4th row	Straight / Heterosexual
5th row	Prefer to self-describe:

Common Values

Value	Count	Frequency (%)
Straight / Heterosexual	32	64.0%
Bisexual	4	8.0%
Prefer to self-describe:	3	6.0%
Bisexual;Straight / Heterosexual	2	4.0%
Gay or Lesbian	1	2.0%
Prefer to self-describe:;Queer	1	2.0%
Prefer not to say	1	2.0%
(Missing)	6	12.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
	34	27.2%
heterosexual	34	27.2%
straight	32	25.6%
prefer	5	4.0%
to	5	4.0%
bisexual	4	3.2%
self-describe	3	2.4%
bisexual;straight	2	1.6%
gay	1	0.8%
or	1	0.8%
Other values (4)	4	3.2%

Most occurring characters

Value	Count	Frequency (%)
e	133	13.8%
t	108	11.2%
r	84	8.7%
	81	8.4%
a	77	8.0%
s	50	5.2%
i	45	4.7%
l	44	4.6%
o	41	4.2%
u	41	4.2%
Other values (20)	261	27.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	757	78.4%
Uppercase Letter	82	8.5%
Space Separator	81	8.4%
Other Punctuation	41	4.2%
Dash Punctuation	4	0.4%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	133	17.6%
t	108	14.3%
r	84	11.1%
a	77	10.2%
s	50	6.6%
i	45	5.9%
l	44	5.8%
o	41	5.4%
u	41	5.4%
x	40	5.3%
Other values (8)	94	12.4%

Uppercase Letter

Value	Count	Frequency (%)
S	34	41.5%
H	34	41.5%
B	6	7.3%
P	5	6.1%
G	1	1.2%
L	1	1.2%
Q	1	1.2%

Other Punctuation

Value	Count	Frequency (%)
/	34	82.9%
:	4	9.8%
;	3	7.3%

Space Separator

Value	Count	Frequency (%)
	81	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	4	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	839	86.9%
Common	126	13.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	133	15.9%
t	108	12.9%
r	84	10.0%
a	77	9.2%
s	50	6.0%
i	45	5.4%
l	44	5.2%
o	41	4.9%
u	41	4.9%
x	40	4.8%
Other values (15)	176	21.0%

Common

Value	Count	Frequency (%)
	81	64.3%
/	34	27.0%
:	4	3.2%
-	4	3.2%
;	3	2.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	965	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	133	13.8%
t	108	11.2%
r	84	8.7%
	81	8.4%
a	77	8.0%
s	50	5.2%
i	45	4.7%
l	44	4.6%
o	41	4.2%
u	41	4.2%
Other values (20)	261	27.0%

Ethnicity
Categorical

HIGH CORRELATION MISSING

Distinct	13
Distinct (%)	29.5%
Missing	6
Missing (%)	12.0%
Memory size	528.0 B

European	11
White	10
White;European	7
Middle Eastern	4
White;North American	3
Other values (8)	9

Length

Max length	50
Median length	31
Mean length	12.136364
Min length	5

Characters and Unicode

Total characters	534
Distinct characters	31
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	7 ?
Unique (%)	15.9%

Sample

1st row	White
2nd row	White
3rd row	Or, in your own words:
4th row	Indian
5th row	Indian

Common Values

Value	Count	Frequency (%)
European	11	22.0%
White	10	20.0%
White;European	7	14.0%
Middle Eastern	4	8.0%
White;North American	3	6.0%
Indian	2	4.0%
Or, in your own words:	1	2.0%
White;European;Middle Eastern;Ethnoreligious group	1	2.0%
Prefer not to say	1	2.0%
European;Ethnoreligious group	1	2.0%
Other values (3)	3	6.0%
(Missing)	6	12.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
european	11	17.5%
white	10	15.9%
white;european	7	11.1%
middle	4	6.3%
eastern	4	6.3%
american	4	6.3%
white;north	3	4.8%
indian	2	3.2%
group	2	3.2%
not	1	1.6%
Other values (15)	15	23.8%

Most occurring characters

Value	Count	Frequency (%)
e	61	11.4%
r	44	8.2%
n	42	7.9%
i	41	7.7%
a	37	6.9%
t	36	6.7%
o	36	6.7%
E	29	5.4%
h	28	5.2%
u	26	4.9%
Other values (21)	154	28.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	425	79.6%
Uppercase Letter	71	13.3%
Space Separator	19	3.6%
Other Punctuation	19	3.6%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	61	14.4%
r	44	10.4%
n	42	9.9%
i	41	9.6%
a	37	8.7%
t	36	8.5%
o	36	8.5%
h	28	6.6%
u	26	6.1%
p	23	5.4%
Other values (9)	51	12.0%

Uppercase Letter

Value	Count	Frequency (%)
E	29	40.8%
W	22	31.0%
A	7	9.9%
M	5	7.0%
N	4	5.6%
I	2	2.8%
O	1	1.4%
P	1	1.4%

Other Punctuation

Value	Count	Frequency (%)
;	17	89.5%
,	1	5.3%
:	1	5.3%

Space Separator

Value	Count	Frequency (%)
	19	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	496	92.9%
Common	38	7.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	61	12.3%
r	44	8.9%
n	42	8.5%
i	41	8.3%
a	37	7.5%
t	36	7.3%
o	36	7.3%
E	29	5.8%
h	28	5.6%
u	26	5.2%
Other values (17)	116	23.4%

Common

Value	Count	Frequency (%)
	19	50.0%
;	17	44.7%
,	1	2.6%
:	1	2.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	534	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	61	11.4%
r	44	8.2%
n	42	7.9%
i	41	7.7%
a	37	6.9%
t	36	6.7%
o	36	6.7%
E	29	5.4%
h	28	5.2%
u	26	4.9%
Other values (21)	154	28.8%

Accessibility
Categorical

HIGH CORRELATION IMBALANCE MISSING

Distinct	3
Distinct (%)	7.0%
Missing	7
Missing (%)	14.0%
Memory size	528.0 B

None of the above	40
Or, in your own words:	2
I am deaf / hard of hearing	1

Length

Max length	27
Median length	17
Mean length	17.465116
Min length	17

Characters and Unicode

Total characters	751
Distinct characters	25
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	2.3%

Sample

1st row	None of the above
2nd row	None of the above
3rd row	Or, in your own words:
4th row	None of the above
5th row	None of the above

Common Values

Value	Count	Frequency (%)
None of the above	40	80.0%
Or, in your own words:	2	4.0%
I am deaf / hard of hearing	1	2.0%
(Missing)	7	14.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
of	41	23.2%
none	40	22.6%
the	40	22.6%
above	40	22.6%
or	2	1.1%
in	2	1.1%
your	2	1.1%
own	2	1.1%
words	2	1.1%
i	1	0.6%
Other values (5)	5	2.8%

Most occurring characters

Value	Count	Frequency (%)
	134	17.8%
o	127	16.9%
e	122	16.2%
n	45	6.0%
a	44	5.9%
f	42	5.6%
h	42	5.6%
N	40	5.3%
t	40	5.3%
b	40	5.3%
Other values (15)	75	10.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	569	75.8%
Space Separator	134	17.8%
Uppercase Letter	43	5.7%
Other Punctuation	5	0.7%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	127	22.3%
e	122	21.4%
n	45	7.9%
a	44	7.7%
f	42	7.4%
h	42	7.4%
t	40	7.0%
b	40	7.0%
v	40	7.0%
r	8	1.4%
Other values (8)	19	3.3%

Uppercase Letter

Value	Count	Frequency (%)
N	40	93.0%
O	2	4.7%
I	1	2.3%

Other Punctuation

Value	Count	Frequency (%)
,	2	40.0%
:	2	40.0%
/	1	20.0%

Space Separator

Value	Count	Frequency (%)
	134	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	612	81.5%
Common	139	18.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	127	20.8%
e	122	19.9%
n	45	7.4%
a	44	7.2%
f	42	6.9%
h	42	6.9%
N	40	6.5%
t	40	6.5%
b	40	6.5%
v	40	6.5%
Other values (11)	30	4.9%

Common

Value	Count	Frequency (%)
	134	96.4%
,	2	1.4%
:	2	1.4%
/	1	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	751	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	134	17.8%
o	127	16.9%
e	122	16.2%
n	45	6.0%
a	44	5.9%
f	42	5.6%
h	42	5.6%
N	40	5.3%
t	40	5.3%
b	40	5.3%
Other values (15)	75	10.0%

MentalHealth
Categorical

HIGH CORRELATION MISSING

Distinct	8
Distinct (%)	18.6%
Missing	7
Missing (%)	14.0%
Memory size	528.0 B

None of the above	28
I have a mood or emotional disorder (e.g., depression, bipolar disorder, etc.)	4
I have a mood or emotional disorder (e.g., depression, bipolar disorder, etc.);I have an anxiety disorder	3
Or, in your own words:	2
I have a mood or emotional disorder (e.g., depression, bipolar disorder, etc.);I have an anxiety disorder;I have a concentration and/or memory disorder (e.g., ADHD, etc.)	2
Other values (3)	4

Length

Max length	170
Median length	17
Mean length	40.255814
Min length	17

Characters and Unicode

Total characters	1731
Distinct characters	37
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	4.7%

Sample

1st row	I have a mood or emotional disorder (e.g., depression, bipolar disorder, etc.);I have an anxiety disorder
2nd row	None of the above
3rd row	Or, in your own words:
4th row	None of the above
5th row	None of the above

Common Values

Value	Count	Frequency (%)
None of the above	28	56.0%
I have a mood or emotional disorder (e.g., depression, bipolar disorder, etc.)	4	8.0%
I have a mood or emotional disorder (e.g., depression, bipolar disorder, etc.);I have an anxiety disorder	3	6.0%
Or, in your own words:	2	4.0%
I have a mood or emotional disorder (e.g., depression, bipolar disorder, etc.);I have an anxiety disorder;I have a concentration and/or memory disorder (e.g., ADHD, etc.)	2	4.0%
I have an anxiety disorder	2	4.0%
I have a concentration and/or memory disorder (e.g., ADHD, etc.);I have learning differences (e.g., Dyslexic, Dyslexia, etc.)	1	2.0%
I have autism / an autism spectrum disorder (e.g. Asperger's, etc.)	1	2.0%
(Missing)	7	14.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
none	28	9.2%
the	28	9.2%
above	28	9.2%
of	28	9.2%
disorder	27	8.8%
have	21	6.9%
e.g	14	4.6%
i	13	4.2%
a	12	3.9%
or	11	3.6%
Other values (25)	96	31.4%

Most occurring characters

Value	Count	Frequency (%)
	263	15.2%
e	211	12.2%
o	194	11.2%
r	105	6.1%
a	104	6.0%
d	82	4.7%
n	80	4.6%
i	74	4.3%
t	67	3.9%
s	57	3.3%
Other values (27)	494	28.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1278	73.8%
Space Separator	263	15.2%
Other Punctuation	96	5.5%
Uppercase Letter	66	3.8%
Open Punctuation	14	0.8%
Close Punctuation	14	0.8%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	211	16.5%
o	194	15.2%
r	105	8.2%
a	104	8.1%
d	82	6.4%
n	80	6.3%
i	74	5.8%
t	67	5.2%
s	57	4.5%
h	49	3.8%
Other values (12)	255	20.0%

Other Punctuation

Value	Count	Frequency (%)
.	42	43.8%
,	39	40.6%
;	8	8.3%
/	4	4.2%
:	2	2.1%
'	1	1.0%

Uppercase Letter

Value	Count	Frequency (%)
N	28	42.4%
I	21	31.8%
D	8	12.1%
A	4	6.1%
H	3	4.5%
O	2	3.0%

Space Separator

Value	Count	Frequency (%)
	263	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	14	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	14	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1344	77.6%
Common	387	22.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	211	15.7%
o	194	14.4%
r	105	7.8%
a	104	7.7%
d	82	6.1%
n	80	6.0%
i	74	5.5%
t	67	5.0%
s	57	4.2%
h	49	3.6%
Other values (18)	321	23.9%

Common

Value	Count	Frequency (%)
	263	68.0%
.	42	10.9%
,	39	10.1%
(	14	3.6%
)	14	3.6%
;	8	2.1%
/	4	1.0%
:	2	0.5%
'	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1731	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	263	15.2%
e	211	12.2%
o	194	11.2%
r	105	6.1%
a	104	6.0%
d	82	4.7%
n	80	4.6%
i	74	4.3%
t	67	3.9%
s	57	3.3%
Other values (27)	494	28.5%

TBranch
Boolean

HIGH CORRELATION MISSING

Distinct	2
Distinct (%)	6.5%
Missing	19
Missing (%)	38.0%
Memory size	228.0 B

True	18
False	13
(Missing)	19

Common Values (Table)
Common Values (Plot)

Value	Count	Frequency (%)
True	18	36.0%
False	13	26.0%
(Missing)	19	38.0%

ICorPM
Categorical

HIGH CORRELATION IMBALANCE MISSING

Distinct	2
Distinct (%)	11.8%
Missing	33
Missing (%)	66.0%
Memory size	528.0 B

Independent contributor	16
People manager	1

Length

Max length	23
Median length	23
Mean length	22.470588
Min length	14

Characters and Unicode

Total characters	382
Distinct characters	18
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	5.9%

Sample

1st row	Independent contributor
2nd row	People manager
3rd row	Independent contributor
4th row	Independent contributor
5th row	Independent contributor

Common Values

Value	Count	Frequency (%)
Independent contributor	16	32.0%
People manager	1	2.0%
(Missing)	33	66.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
independent	16	47.1%
contributor	16	47.1%
people	1	2.9%
manager	1	2.9%

Most occurring characters

Value	Count	Frequency (%)
n	65	17.0%
e	51	13.4%
t	48	12.6%
r	33	8.6%
o	33	8.6%
d	32	8.4%
p	17	4.5%
	17	4.5%
b	16	4.2%
u	16	4.2%
Other values (8)	54	14.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	348	91.1%
Space Separator	17	4.5%
Uppercase Letter	17	4.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	65	18.7%
e	51	14.7%
t	48	13.8%
r	33	9.5%
o	33	9.5%
d	32	9.2%
p	17	4.9%
b	16	4.6%
u	16	4.6%
i	16	4.6%
Other values (5)	21	6.0%

Uppercase Letter

Value	Count	Frequency (%)
I	16	94.1%
P	1	5.9%

Space Separator

Value	Count	Frequency (%)
	17	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	365	95.5%
Common	17	4.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	65	17.8%
e	51	14.0%
t	48	13.2%
r	33	9.0%
o	33	9.0%
d	32	8.8%
p	17	4.7%
b	16	4.4%
u	16	4.4%
I	16	4.4%
Other values (7)	38	10.4%

Common

Value	Count	Frequency (%)
	17	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	382	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	65	17.0%
e	51	13.4%
t	48	12.6%
r	33	8.6%
o	33	8.6%
d	32	8.4%
p	17	4.5%
	17	4.5%
b	16	4.2%
u	16	4.2%
Other values (8)	54	14.1%

WorkExp
Real number (ℝ)

HIGH CORRELATION MISSING

Distinct	12
Distinct (%)	66.7%
Missing	32
Missing (%)	64.0%
Infinite	0
Infinite (%)	0.0%
Mean	10.833333

Minimum	3
Maximum	28
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	528.0 B

Quantile statistics

Minimum	3
5-th percentile	3
Q1	5
median	6.5
Q3	14.75
95-th percentile	23.75
Maximum	28
Range	25
Interquartile range (IQR)	9.75

Descriptive statistics

Standard deviation	7.964997
Coefficient of variation (CV)	0.73523049
Kurtosis	-0.46446422
Mean	10.833333
Median Absolute Deviation (MAD)	3
Skewness	0.92673388
Sum	195
Variance	63.441176
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=12)

Value	Count	Frequency (%)
5	4	8.0%
6	2	4.0%
14	2	4.0%
3	2	4.0%
15	1	2.0%
4	1	2.0%
23	1	2.0%
9	1	2.0%
22	1	2.0%
21	1	2.0%
Other values (2)	2	4.0%
(Missing)	32	64.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
3	2	4.0%
4	1	2.0%
5	4	8.0%
6	2	4.0%
7	1	2.0%
9	1	2.0%
14	2	4.0%
15	1	2.0%
21	1	2.0%
22	1	2.0%

Value	Count	Frequency (%)
28	1	2.0%
23	1	2.0%
22	1	2.0%
21	1	2.0%
15	1	2.0%
14	2	4.0%
9	1	2.0%
7	1	2.0%
6	2	4.0%
5	4	8.0%

Knowledge_1
Categorical

HIGH CORRELATION MISSING

Distinct	3
Distinct (%)	16.7%
Missing	32
Missing (%)	64.0%
Memory size	528.0 B

Agree	10
Strongly agree	5
Neither agree nor disagree	3

Length

Max length	26
Median length	5
Mean length	11
Min length	5

Characters and Unicode

Total characters	198
Distinct characters	17
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Agree
2nd row	Strongly agree
3rd row	Neither agree nor disagree
4th row	Agree
5th row	Agree

Common Values

Value	Count	Frequency (%)
Agree	10	20.0%
Strongly agree	5	10.0%
Neither agree nor disagree	3	6.0%
(Missing)	32	64.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
agree	18	56.2%
strongly	5	15.6%
neither	3	9.4%
nor	3	9.4%
disagree	3	9.4%

Most occurring characters

Value	Count	Frequency (%)
e	48	24.2%
r	32	16.2%
g	26	13.1%
	14	7.1%
a	11	5.6%
A	10	5.1%
t	8	4.0%
o	8	4.0%
n	8	4.0%
i	6	3.0%
Other values (7)	27	13.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	166	83.8%
Uppercase Letter	18	9.1%
Space Separator	14	7.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	48	28.9%
r	32	19.3%
g	26	15.7%
a	11	6.6%
t	8	4.8%
o	8	4.8%
n	8	4.8%
i	6	3.6%
l	5	3.0%
y	5	3.0%
Other values (3)	9	5.4%

Uppercase Letter

Value	Count	Frequency (%)
A	10	55.6%
S	5	27.8%
N	3	16.7%

Space Separator

Value	Count	Frequency (%)
	14	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	184	92.9%
Common	14	7.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	48	26.1%
r	32	17.4%
g	26	14.1%
a	11	6.0%
A	10	5.4%
t	8	4.3%
o	8	4.3%
n	8	4.3%
i	6	3.3%
l	5	2.7%
Other values (6)	22	12.0%

Common

Value	Count	Frequency (%)
	14	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	198	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	48	24.2%
r	32	16.2%
g	26	13.1%
	14	7.1%
a	11	5.6%
A	10	5.1%
t	8	4.0%
o	8	4.0%
n	8	4.0%
i	6	3.0%
Other values (7)	27	13.6%

Knowledge_2
Categorical

HIGH CORRELATION MISSING

Distinct	4
Distinct (%)	22.2%
Missing	32
Missing (%)	64.0%
Memory size	528.0 B

Agree	7
Neither agree nor disagree	5
Disagree	4
Strongly agree	2

Length

Max length	26
Median length	14
Mean length	12.5
Min length	5

Characters and Unicode

Total characters	225
Distinct characters	18
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Disagree
2nd row	Agree
3rd row	Disagree
4th row	Agree
5th row	Neither agree nor disagree

Common Values

Value	Count	Frequency (%)
Agree	7	14.0%
Neither agree nor disagree	5	10.0%
Disagree	4	8.0%
Strongly agree	2	4.0%
(Missing)	32	64.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
agree	14	40.0%
disagree	9	25.7%
neither	5	14.3%
nor	5	14.3%
strongly	2	5.7%

Most occurring characters

Value	Count	Frequency (%)
e	56	24.9%
r	35	15.6%
g	25	11.1%
	17	7.6%
a	16	7.1%
i	14	6.2%
s	9	4.0%
o	7	3.1%
n	7	3.1%
A	7	3.1%
Other values (8)	32	14.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	190	84.4%
Uppercase Letter	18	8.0%
Space Separator	17	7.6%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	56	29.5%
r	35	18.4%
g	25	13.2%
a	16	8.4%
i	14	7.4%
s	9	4.7%
o	7	3.7%
n	7	3.7%
t	7	3.7%
h	5	2.6%
Other values (3)	9	4.7%

Uppercase Letter

Value	Count	Frequency (%)
A	7	38.9%
N	5	27.8%
D	4	22.2%
S	2	11.1%

Space Separator

Value	Count	Frequency (%)
	17	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	208	92.4%
Common	17	7.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	56	26.9%
r	35	16.8%
g	25	12.0%
a	16	7.7%
i	14	6.7%
s	9	4.3%
o	7	3.4%
n	7	3.4%
A	7	3.4%
t	7	3.4%
Other values (7)	25	12.0%

Common

Value	Count	Frequency (%)
	17	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	225	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	56	24.9%
r	35	15.6%
g	25	11.1%
	17	7.6%
a	16	7.1%
i	14	6.2%
s	9	4.0%
o	7	3.1%
n	7	3.1%
A	7	3.1%
Other values (8)	32	14.2%

Knowledge_3
Categorical

HIGH CORRELATION MISSING

Distinct	5
Distinct (%)	27.8%
Missing	32
Missing (%)	64.0%
Memory size	528.0 B

Neither agree nor disagree	6
Agree	5
Disagree	5
Strongly agree	1
Strongly disagree	1

Length

Max length	26
Median length	17
Mean length	14
Min length	5

Characters and Unicode

Total characters	252
Distinct characters	18
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	11.1%

Sample

1st row	Agree
2nd row	Disagree
3rd row	Strongly agree
4th row	Neither agree nor disagree
5th row	Neither agree nor disagree

Common Values

Value	Count	Frequency (%)
Neither agree nor disagree	6	12.0%
Agree	5	10.0%
Disagree	5	10.0%
Strongly agree	1	2.0%
Strongly disagree	1	2.0%
(Missing)	32	64.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
agree	12	31.6%
disagree	12	31.6%
neither	6	15.8%
nor	6	15.8%
strongly	2	5.3%

Most occurring characters

Value	Count	Frequency (%)
e	60	23.8%
r	38	15.1%
g	26	10.3%
	20	7.9%
a	19	7.5%
i	18	7.1%
s	12	4.8%
n	8	3.2%
t	8	3.2%
o	8	3.2%
Other values (8)	35	13.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	214	84.9%
Space Separator	20	7.9%
Uppercase Letter	18	7.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	60	28.0%
r	38	17.8%
g	26	12.1%
a	19	8.9%
i	18	8.4%
s	12	5.6%
n	8	3.7%
t	8	3.7%
o	8	3.7%
d	7	3.3%
Other values (3)	10	4.7%

Uppercase Letter

Value	Count	Frequency (%)
N	6	33.3%
A	5	27.8%
D	5	27.8%
S	2	11.1%

Space Separator

Value	Count	Frequency (%)
	20	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	232	92.1%
Common	20	7.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	60	25.9%
r	38	16.4%
g	26	11.2%
a	19	8.2%
i	18	7.8%
s	12	5.2%
n	8	3.4%
t	8	3.4%
o	8	3.4%
d	7	3.0%
Other values (7)	28	12.1%

Common

Value	Count	Frequency (%)
	20	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	252	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	60	23.8%
r	38	15.1%
g	26	10.3%
	20	7.9%
a	19	7.5%
i	18	7.1%
s	12	4.8%
n	8	3.2%
t	8	3.2%
o	8	3.2%
Other values (8)	35	13.9%

Knowledge_4
Categorical

HIGH CORRELATION MISSING

Distinct	4
Distinct (%)	22.2%
Missing	32
Missing (%)	64.0%
Memory size	528.0 B

Agree	6
Disagree	5
Neither agree nor disagree	4
Strongly agree	3

Length

Max length	26
Median length	14
Mean length	12
Min length	5

Characters and Unicode

Total characters	216
Distinct characters	18
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Agree
2nd row	Agree
3rd row	Strongly agree
4th row	Neither agree nor disagree
5th row	Neither agree nor disagree

Common Values

Value	Count	Frequency (%)
Agree	6	12.0%
Disagree	5	10.0%
Neither agree nor disagree	4	8.0%
Strongly agree	3	6.0%
(Missing)	32	64.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
agree	13	39.4%
disagree	9	27.3%
neither	4	12.1%
nor	4	12.1%
strongly	3	9.1%

Most occurring characters

Value	Count	Frequency (%)
e	52	24.1%
r	33	15.3%
g	25	11.6%
a	16	7.4%
	15	6.9%
i	13	6.0%
s	9	4.2%
t	7	3.2%
o	7	3.2%
n	7	3.2%
Other values (8)	32	14.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	183	84.7%
Uppercase Letter	18	8.3%
Space Separator	15	6.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	52	28.4%
r	33	18.0%
g	25	13.7%
a	16	8.7%
i	13	7.1%
s	9	4.9%
t	7	3.8%
o	7	3.8%
n	7	3.8%
h	4	2.2%
Other values (3)	10	5.5%

Uppercase Letter

Value	Count	Frequency (%)
A	6	33.3%
D	5	27.8%
N	4	22.2%
S	3	16.7%

Space Separator

Value	Count	Frequency (%)
	15	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	201	93.1%
Common	15	6.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	52	25.9%
r	33	16.4%
g	25	12.4%
a	16	8.0%
i	13	6.5%
s	9	4.5%
t	7	3.5%
o	7	3.5%
n	7	3.5%
A	6	3.0%
Other values (7)	26	12.9%

Common

Value	Count	Frequency (%)
	15	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	216	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	52	24.1%
r	33	15.3%
g	25	11.6%
a	16	7.4%
	15	6.9%
i	13	6.0%
s	9	4.2%
t	7	3.2%
o	7	3.2%
n	7	3.2%
Other values (8)	32	14.8%

Knowledge_5
Categorical

HIGH CORRELATION MISSING

Distinct	4
Distinct (%)	22.2%
Missing	32
Missing (%)	64.0%
Memory size	528.0 B

Agree	6
Strongly agree	4
Neither agree nor disagree	4
Disagree	4

Length

Max length	26
Median length	14
Mean length	12.333333
Min length	5

Characters and Unicode

Total characters	222
Distinct characters	18
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Agree
2nd row	Agree
3rd row	Strongly agree
4th row	Neither agree nor disagree
5th row	Neither agree nor disagree

Common Values

Value	Count	Frequency (%)
Agree	6	12.0%
Strongly agree	4	8.0%
Neither agree nor disagree	4	8.0%
Disagree	4	8.0%
(Missing)	32	64.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
agree	14	41.2%
disagree	8	23.5%
strongly	4	11.8%
neither	4	11.8%
nor	4	11.8%

Most occurring characters

Value	Count	Frequency (%)
e	52	23.4%
r	34	15.3%
g	26	11.7%
	16	7.2%
a	16	7.2%
i	12	5.4%
s	8	3.6%
t	8	3.6%
o	8	3.6%
n	8	3.6%
Other values (8)	34	15.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	188	84.7%
Uppercase Letter	18	8.1%
Space Separator	16	7.2%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	52	27.7%
r	34	18.1%
g	26	13.8%
a	16	8.5%
i	12	6.4%
s	8	4.3%
t	8	4.3%
o	8	4.3%
n	8	4.3%
d	4	2.1%
Other values (3)	12	6.4%

Uppercase Letter

Value	Count	Frequency (%)
A	6	33.3%
N	4	22.2%
S	4	22.2%
D	4	22.2%

Space Separator

Value	Count	Frequency (%)
	16	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	206	92.8%
Common	16	7.2%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	52	25.2%
r	34	16.5%
g	26	12.6%
a	16	7.8%
i	12	5.8%
s	8	3.9%
t	8	3.9%
o	8	3.9%
n	8	3.9%
A	6	2.9%
Other values (7)	28	13.6%

Common

Value	Count	Frequency (%)
	16	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	222	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	52	23.4%
r	34	15.3%
g	26	11.7%
	16	7.2%
a	16	7.2%
i	12	5.4%
s	8	3.6%
t	8	3.6%
o	8	3.6%
n	8	3.6%
Other values (8)	34	15.3%

Knowledge_6
Categorical

HIGH CORRELATION MISSING

Distinct	4
Distinct (%)	22.2%
Missing	32
Missing (%)	64.0%
Memory size	528.0 B

Agree	9
Strongly agree	4
Disagree	3
Neither agree nor disagree	2

Length

Max length	26
Median length	20
Mean length	9.8333333
Min length	5

Characters and Unicode

Total characters	177
Distinct characters	18
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Agree
2nd row	Agree
3rd row	Agree
4th row	Agree
5th row	Neither agree nor disagree

Common Values

Value	Count	Frequency (%)
Agree	9	18.0%
Strongly agree	4	8.0%
Disagree	3	6.0%
Neither agree nor disagree	2	4.0%
(Missing)	32	64.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
agree	15	53.6%
disagree	5	17.9%
strongly	4	14.3%
neither	2	7.1%
nor	2	7.1%

Most occurring characters

Value	Count	Frequency (%)
e	44	24.9%
r	28	15.8%
g	24	13.6%
a	11	6.2%
	10	5.6%
A	9	5.1%
i	7	4.0%
t	6	3.4%
o	6	3.4%
n	6	3.4%
Other values (8)	26	14.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	149	84.2%
Uppercase Letter	18	10.2%
Space Separator	10	5.6%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	44	29.5%
r	28	18.8%
g	24	16.1%
a	11	7.4%
i	7	4.7%
t	6	4.0%
o	6	4.0%
n	6	4.0%
s	5	3.4%
y	4	2.7%
Other values (3)	8	5.4%

Uppercase Letter

Value	Count	Frequency (%)
A	9	50.0%
S	4	22.2%
D	3	16.7%
N	2	11.1%

Space Separator

Value	Count	Frequency (%)
	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	167	94.4%
Common	10	5.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	44	26.3%
r	28	16.8%
g	24	14.4%
a	11	6.6%
A	9	5.4%
i	7	4.2%
t	6	3.6%
o	6	3.6%
n	6	3.6%
s	5	3.0%
Other values (7)	21	12.6%

Common

Value	Count	Frequency (%)
	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	177	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	44	24.9%
r	28	15.8%
g	24	13.6%
a	11	6.2%
	10	5.6%
A	9	5.1%
i	7	4.0%
t	6	3.4%
o	6	3.4%
n	6	3.4%
Other values (8)	26	14.7%

Knowledge_7
Categorical

HIGH CORRELATION MISSING

Distinct	4
Distinct (%)	22.2%
Missing	32
Missing (%)	64.0%
Memory size	528.0 B

Agree	8
Disagree	6
Neither agree nor disagree	3
Strongly agree	1

Length

Max length	26
Median length	14
Mean length	10
Min length	5

Characters and Unicode

Total characters	180
Distinct characters	18
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	5.6%

Sample

1st row	Disagree
2nd row	Agree
3rd row	Disagree
4th row	Agree
5th row	Neither agree nor disagree

Common Values

Value	Count	Frequency (%)
Agree	8	16.0%
Disagree	6	12.0%
Neither agree nor disagree	3	6.0%
Strongly agree	1	2.0%
(Missing)	32	64.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
agree	12	42.9%
disagree	9	32.1%
neither	3	10.7%
nor	3	10.7%
strongly	1	3.6%

Most occurring characters

Value	Count	Frequency (%)
e	48	26.7%
r	28	15.6%
g	22	12.2%
a	13	7.2%
i	12	6.7%
	10	5.6%
s	9	5.0%
A	8	4.4%
D	6	3.3%
o	4	2.2%
Other values (8)	20	11.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	152	84.4%
Uppercase Letter	18	10.0%
Space Separator	10	5.6%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	48	31.6%
r	28	18.4%
g	22	14.5%
a	13	8.6%
i	12	7.9%
s	9	5.9%
o	4	2.6%
n	4	2.6%
t	4	2.6%
h	3	2.0%
Other values (3)	5	3.3%

Uppercase Letter

Value	Count	Frequency (%)
A	8	44.4%
D	6	33.3%
N	3	16.7%
S	1	5.6%

Space Separator

Value	Count	Frequency (%)
	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	170	94.4%
Common	10	5.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	48	28.2%
r	28	16.5%
g	22	12.9%
a	13	7.6%
i	12	7.1%
s	9	5.3%
A	8	4.7%
D	6	3.5%
o	4	2.4%
n	4	2.4%
Other values (7)	16	9.4%

Common

Value	Count	Frequency (%)
	10	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	180	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	48	26.7%
r	28	15.6%
g	22	12.2%
a	13	7.2%
i	12	6.7%
	10	5.6%
s	9	5.0%
A	8	4.4%
D	6	3.3%
o	4	2.2%
Other values (8)	20	11.1%

Frequency_1
Categorical

HIGH CORRELATION MISSING

Distinct	4
Distinct (%)	22.2%
Missing	32
Missing (%)	64.0%
Memory size	528.0 B

1-2 times a week	13
Never	3
3-5 times a week	1
10+ times a week	1

Length

Max length	16
Median length	16
Mean length	14.166667
Min length	5

Characters and Unicode

Total characters	255
Distinct characters	19
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	11.1%

Sample

1st row	3-5 times a week
2nd row	10+ times a week
3rd row	Never
4th row	1-2 times a week
5th row	1-2 times a week

Common Values

Value	Count	Frequency (%)
1-2 times a week	13	26.0%
Never	3	6.0%
3-5 times a week	1	2.0%
10+ times a week	1	2.0%
(Missing)	32	64.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
times	15	23.8%
a	15	23.8%
week	15	23.8%
1-2	13	20.6%
never	3	4.8%
3-5	1	1.6%
10	1	1.6%

Most occurring characters

Value	Count	Frequency (%)
e	51	20.0%
	45	17.6%
a	15	5.9%
w	15	5.9%
k	15	5.9%
t	15	5.9%
i	15	5.9%
m	15	5.9%
s	15	5.9%
1	14	5.5%
Other values (9)	40	15.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	162	63.5%
Space Separator	45	17.6%
Decimal Number	30	11.8%
Dash Punctuation	14	5.5%
Uppercase Letter	3	1.2%
Math Symbol	1	0.4%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	51	31.5%
a	15	9.3%
w	15	9.3%
k	15	9.3%
t	15	9.3%
i	15	9.3%
m	15	9.3%
s	15	9.3%
v	3	1.9%
r	3	1.9%

Decimal Number

Value	Count	Frequency (%)
1	14	46.7%
2	13	43.3%
3	1	3.3%
5	1	3.3%
0	1	3.3%

Space Separator

Value	Count	Frequency (%)
	45	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	14	100.0%

Uppercase Letter

Value	Count	Frequency (%)
N	3	100.0%

Math Symbol

Value	Count	Frequency (%)
+	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	165	64.7%
Common	90	35.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	51	30.9%
a	15	9.1%
w	15	9.1%
k	15	9.1%
t	15	9.1%
i	15	9.1%
m	15	9.1%
s	15	9.1%
N	3	1.8%
v	3	1.8%

Common

Value	Count	Frequency (%)
	45	50.0%
1	14	15.6%
-	14	15.6%
2	13	14.4%
3	1	1.1%
5	1	1.1%
0	1	1.1%
+	1	1.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	255	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	51	20.0%
	45	17.6%
a	15	5.9%
w	15	5.9%
k	15	5.9%
t	15	5.9%
i	15	5.9%
m	15	5.9%
s	15	5.9%
1	14	5.5%
Other values (9)	40	15.7%

Frequency_2
Categorical

HIGH CORRELATION MISSING

Distinct	5
Distinct (%)	27.8%
Missing	32
Missing (%)	64.0%
Memory size	528.0 B

1-2 times a week	9
3-5 times a week	3
10+ times a week	3
6-10 times a week	2
Never	1

Length

Max length	17
Median length	16
Mean length	15.5
Min length	5

Characters and Unicode

Total characters	279
Distinct characters	20
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	5.6%

Sample

1st row	3-5 times a week
2nd row	10+ times a week
3rd row	Never
4th row	10+ times a week
5th row	3-5 times a week

Common Values

Value	Count	Frequency (%)
1-2 times a week	9	18.0%
3-5 times a week	3	6.0%
10+ times a week	3	6.0%
6-10 times a week	2	4.0%
Never	1	2.0%
(Missing)	32	64.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
times	17	24.6%
a	17	24.6%
week	17	24.6%
1-2	9	13.0%
3-5	3	4.3%
10	3	4.3%
6-10	2	2.9%
never	1	1.4%

Most occurring characters

Value	Count	Frequency (%)
e	53	19.0%
	51	18.3%
w	17	6.1%
k	17	6.1%
t	17	6.1%
i	17	6.1%
m	17	6.1%
s	17	6.1%
a	17	6.1%
-	14	5.0%
Other values (10)	42	15.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	174	62.4%
Space Separator	51	18.3%
Decimal Number	36	12.9%
Dash Punctuation	14	5.0%
Math Symbol	3	1.1%
Uppercase Letter	1	0.4%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	53	30.5%
w	17	9.8%
k	17	9.8%
t	17	9.8%
i	17	9.8%
m	17	9.8%
s	17	9.8%
a	17	9.8%
v	1	0.6%
r	1	0.6%

Decimal Number

Value	Count	Frequency (%)
1	14	38.9%
2	9	25.0%
0	5	13.9%
3	3	8.3%
5	3	8.3%
6	2	5.6%

Space Separator

Value	Count	Frequency (%)
	51	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	14	100.0%

Math Symbol

Value	Count	Frequency (%)
+	3	100.0%

Uppercase Letter

Value	Count	Frequency (%)
N	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	175	62.7%
Common	104	37.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	53	30.3%
w	17	9.7%
k	17	9.7%
t	17	9.7%
i	17	9.7%
m	17	9.7%
s	17	9.7%
a	17	9.7%
N	1	0.6%
v	1	0.6%

Common

Value	Count	Frequency (%)
	51	49.0%
-	14	13.5%
1	14	13.5%
2	9	8.7%
0	5	4.8%
3	3	2.9%
5	3	2.9%
+	3	2.9%
6	2	1.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	279	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	53	19.0%
	51	18.3%
w	17	6.1%
k	17	6.1%
t	17	6.1%
i	17	6.1%
m	17	6.1%
s	17	6.1%
a	17	6.1%
-	14	5.0%
Other values (10)	42	15.1%

Frequency_3
Categorical

HIGH CORRELATION MISSING

Distinct	3
Distinct (%)	16.7%
Missing	32
Missing (%)	64.0%
Memory size	528.0 B

1-2 times a week	11
Never	5
3-5 times a week	2

Length

Max length	16
Median length	16
Mean length	12.944444
Min length	5

Characters and Unicode

Total characters	233
Distinct characters	17
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Never
2nd row	3-5 times a week
3rd row	Never
4th row	1-2 times a week
5th row	1-2 times a week

Common Values

Value	Count	Frequency (%)
1-2 times a week	11	22.0%
Never	5	10.0%
3-5 times a week	2	4.0%
(Missing)	32	64.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
times	13	22.8%
a	13	22.8%
week	13	22.8%
1-2	11	19.3%
never	5	8.8%
3-5	2	3.5%

Most occurring characters

Value	Count	Frequency (%)
e	49	21.0%
	39	16.7%
s	13	5.6%
w	13	5.6%
k	13	5.6%
t	13	5.6%
i	13	5.6%
m	13	5.6%
-	13	5.6%
a	13	5.6%
Other values (7)	41	17.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	150	64.4%
Space Separator	39	16.7%
Decimal Number	26	11.2%
Dash Punctuation	13	5.6%
Uppercase Letter	5	2.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	49	32.7%
s	13	8.7%
w	13	8.7%
k	13	8.7%
t	13	8.7%
i	13	8.7%
m	13	8.7%
a	13	8.7%
v	5	3.3%
r	5	3.3%

Decimal Number

Value	Count	Frequency (%)
1	11	42.3%
2	11	42.3%
3	2	7.7%
5	2	7.7%

Space Separator

Value	Count	Frequency (%)
	39	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	13	100.0%

Uppercase Letter

Value	Count	Frequency (%)
N	5	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	155	66.5%
Common	78	33.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	49	31.6%
s	13	8.4%
w	13	8.4%
k	13	8.4%
t	13	8.4%
i	13	8.4%
m	13	8.4%
a	13	8.4%
N	5	3.2%
v	5	3.2%

Common

Value	Count	Frequency (%)
	39	50.0%
-	13	16.7%
1	11	14.1%
2	11	14.1%
3	2	2.6%
5	2	2.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	233	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	49	21.0%
	39	16.7%
s	13	5.6%
w	13	5.6%
k	13	5.6%
t	13	5.6%
i	13	5.6%
m	13	5.6%
-	13	5.6%
a	13	5.6%
Other values (7)	41	17.6%

TimeSearching
Categorical

HIGH CORRELATION MISSING

Distinct	4
Distinct (%)	22.2%
Missing	32
Missing (%)	64.0%
Memory size	528.0 B

30-60 minutes a day	13
15-30 minutes a day	3
60-120 minutes a day	1
Less than 15 minutes a day	1

Length

Max length	26
Median length	19
Mean length	19.444444
Min length	19

Characters and Unicode

Total characters	350
Distinct characters	20
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	11.1%

Sample

1st row	15-30 minutes a day
2nd row	30-60 minutes a day
3rd row	30-60 minutes a day
4th row	60-120 minutes a day
5th row	30-60 minutes a day

Common Values

Value	Count	Frequency (%)
30-60 minutes a day	13	26.0%
15-30 minutes a day	3	6.0%
60-120 minutes a day	1	2.0%
Less than 15 minutes a day	1	2.0%
(Missing)	32	64.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
minutes	18	24.3%
a	18	24.3%
day	18	24.3%
30-60	13	17.6%
15-30	3	4.1%
60-120	1	1.4%
less	1	1.4%
than	1	1.4%
15	1	1.4%

Most occurring characters

Value	Count	Frequency (%)
	56	16.0%
a	37	10.6%
0	31	8.9%
s	20	5.7%
e	19	5.4%
n	19	5.4%
t	19	5.4%
d	18	5.1%
y	18	5.1%
m	18	5.1%
Other values (10)	95	27.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	205	58.6%
Decimal Number	71	20.3%
Space Separator	56	16.0%
Dash Punctuation	17	4.9%
Uppercase Letter	1	0.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	37	18.0%
s	20	9.8%
e	19	9.3%
n	19	9.3%
t	19	9.3%
d	18	8.8%
y	18	8.8%
m	18	8.8%
i	18	8.8%
u	18	8.8%

Decimal Number

Value	Count	Frequency (%)
0	31	43.7%
3	16	22.5%
6	14	19.7%
1	5	7.0%
5	4	5.6%
2	1	1.4%

Space Separator

Value	Count	Frequency (%)
	56	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	17	100.0%

Uppercase Letter

Value	Count	Frequency (%)
L	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	206	58.9%
Common	144	41.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	37	18.0%
s	20	9.7%
e	19	9.2%
n	19	9.2%
t	19	9.2%
d	18	8.7%
y	18	8.7%
m	18	8.7%
i	18	8.7%
u	18	8.7%
Other values (2)	2	1.0%

Common

Value	Count	Frequency (%)
	56	38.9%
0	31	21.5%
-	17	11.8%
3	16	11.1%
6	14	9.7%
1	5	3.5%
5	4	2.8%
2	1	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	350	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	56	16.0%
a	37	10.6%
0	31	8.9%
s	20	5.7%
e	19	5.4%
n	19	5.4%
t	19	5.4%
d	18	5.1%
y	18	5.1%
m	18	5.1%
Other values (10)	95	27.1%

TimeAnswering
Categorical

HIGH CORRELATION MISSING

Distinct	5
Distinct (%)	27.8%
Missing	32
Missing (%)	64.0%
Memory size	528.0 B

15-30 minutes a day	8
30-60 minutes a day	4
60-120 minutes a day	3
Less than 15 minutes a day	2
Over 120 minutes a day	1

Length

Max length	26
Median length	19
Mean length	20.111111
Min length	19

Characters and Unicode

Total characters	362
Distinct characters	23
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	5.6%

Sample

1st row	Over 120 minutes a day
2nd row	60-120 minutes a day
3rd row	Less than 15 minutes a day
4th row	30-60 minutes a day
5th row	30-60 minutes a day

Common Values

Value	Count	Frequency (%)
15-30 minutes a day	8	16.0%
30-60 minutes a day	4	8.0%
60-120 minutes a day	3	6.0%
Less than 15 minutes a day	2	4.0%
Over 120 minutes a day	1	2.0%
(Missing)	32	64.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
minutes	18	23.4%
a	18	23.4%
day	18	23.4%
15-30	8	10.4%
30-60	4	5.2%
60-120	3	3.9%
less	2	2.6%
than	2	2.6%
15	2	2.6%
over	1	1.3%

Most occurring characters

Value	Count	Frequency (%)
	59	16.3%
a	38	10.5%
0	23	6.4%
s	22	6.1%
e	21	5.8%
n	20	5.5%
t	20	5.5%
y	18	5.0%
m	18	5.0%
i	18	5.0%
Other values (13)	105	29.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	215	59.4%
Decimal Number	70	19.3%
Space Separator	59	16.3%
Dash Punctuation	15	4.1%
Uppercase Letter	3	0.8%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	38	17.7%
s	22	10.2%
e	21	9.8%
n	20	9.3%
t	20	9.3%
y	18	8.4%
m	18	8.4%
i	18	8.4%
u	18	8.4%
d	18	8.4%
Other values (3)	4	1.9%

Decimal Number

Value	Count	Frequency (%)
0	23	32.9%
1	14	20.0%
3	12	17.1%
5	10	14.3%
6	7	10.0%
2	4	5.7%

Uppercase Letter

Value	Count	Frequency (%)
L	2	66.7%
O	1	33.3%

Space Separator

Value	Count	Frequency (%)
	59	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	15	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	218	60.2%
Common	144	39.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	38	17.4%
s	22	10.1%
e	21	9.6%
n	20	9.2%
t	20	9.2%
y	18	8.3%
m	18	8.3%
i	18	8.3%
u	18	8.3%
d	18	8.3%
Other values (5)	7	3.2%

Common

Value	Count	Frequency (%)
	59	41.0%
0	23	16.0%
-	15	10.4%
1	14	9.7%
3	12	8.3%
5	10	6.9%
6	7	4.9%
2	4	2.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	362	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	59	16.3%
a	38	10.5%
0	23	6.4%
s	22	6.1%
e	21	5.8%
n	20	5.5%
t	20	5.5%
y	18	5.0%
m	18	5.0%
i	18	5.0%
Other values (13)	105	29.0%

Onboarding
Categorical

HIGH CORRELATION MISSING

Distinct	5
Distinct (%)	27.8%
Missing	32
Missing (%)	64.0%
Memory size	528.0 B

Somewhat long	9
Somewhat short	4
Just right	2
Very long	2
Very short	1

Length

Max length	14
Median length	13.5
Mean length	12.277778
Min length	9

Characters and Unicode

Total characters	221
Distinct characters	19
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	5.6%

Sample

1st row	Somewhat long
2nd row	Just right
3rd row	Somewhat short
4th row	Very short
5th row	Somewhat long

Common Values

Value	Count	Frequency (%)
Somewhat long	9	18.0%
Somewhat short	4	8.0%
Just right	2	4.0%
Very long	2	4.0%
Very short	1	2.0%
(Missing)	32	64.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
somewhat	13	36.1%
long	11	30.6%
short	5	13.9%
very	3	8.3%
just	2	5.6%
right	2	5.6%

Most occurring characters

Value	Count	Frequency (%)
o	29	13.1%
t	22	10.0%
h	20	9.0%
	18	8.1%
e	16	7.2%
S	13	5.9%
g	13	5.9%
m	13	5.9%
w	13	5.9%
a	13	5.9%
Other values (9)	51	23.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	185	83.7%
Space Separator	18	8.1%
Uppercase Letter	18	8.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	29	15.7%
t	22	11.9%
h	20	10.8%
e	16	8.6%
g	13	7.0%
m	13	7.0%
w	13	7.0%
a	13	7.0%
l	11	5.9%
n	11	5.9%
Other values (5)	24	13.0%

Uppercase Letter

Value	Count	Frequency (%)
S	13	72.2%
V	3	16.7%
J	2	11.1%

Space Separator

Value	Count	Frequency (%)
	18	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	203	91.9%
Common	18	8.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	29	14.3%
t	22	10.8%
h	20	9.9%
e	16	7.9%
S	13	6.4%
g	13	6.4%
m	13	6.4%
w	13	6.4%
a	13	6.4%
l	11	5.4%
Other values (8)	40	19.7%

Common

Value	Count	Frequency (%)
	18	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	221	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	29	13.1%
t	22	10.0%
h	20	9.0%
	18	8.1%
e	16	7.2%
S	13	5.9%
g	13	5.9%
m	13	5.9%
w	13	5.9%
a	13	5.9%
Other values (9)	51	23.1%

ProfessionalTech
Categorical

HIGH CORRELATION MISSING

Distinct	14
Distinct (%)	82.4%
Missing	33
Missing (%)	66.0%
Memory size	528.0 B

Continuous integration (CI) and (more often) continuous delivery;Automated testing	3
DevOps function;Microservices;Continuous integration (CI) and (more often) continuous delivery;Automated testing;Observability tools	2
Innersource initiative;DevOps function;Microservices;Developer portal or other central places to find tools/services;Continuous integration (CI) and (more often) continuous delivery;Automated testing;Observability tools	1
Innersource initiative;DevOps function;Microservices;Continuous integration (CI) and (more often) continuous delivery;Automated testing;Observability tools	1
DevOps function;Microservices	1
Other values (9)	9

Length

Max length	219
Median length	132
Mean length	101.82353
Min length	13

Characters and Unicode

Total characters	1731
Distinct characters	32
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	12 ?
Unique (%)	70.6%

Sample

1st row	Innersource initiative;DevOps function;Microservices;Developer portal or other central places to find tools/services;Continuous integration (CI) and (more often) continuous delivery;Automated testing;Observability tools
2nd row	Innersource initiative;DevOps function;Microservices;Continuous integration (CI) and (more often) continuous delivery;Automated testing;Observability tools
3rd row	DevOps function;Microservices
4th row	Continuous integration (CI) and (more often) continuous delivery;Automated testing
5th row	DevOps function;Continuous integration (CI) and (more often) continuous delivery;Automated testing

Common Values

Value	Count	Frequency (%)
Continuous integration (CI) and (more often) continuous delivery;Automated testing	3	6.0%
DevOps function;Microservices;Continuous integration (CI) and (more often) continuous delivery;Automated testing;Observability tools	2	4.0%
Innersource initiative;DevOps function;Microservices;Developer portal or other central places to find tools/services;Continuous integration (CI) and (more often) continuous delivery;Automated testing;Observability tools	1	2.0%
Innersource initiative;DevOps function;Microservices;Continuous integration (CI) and (more often) continuous delivery;Automated testing;Observability tools	1	2.0%
DevOps function;Microservices	1	2.0%
DevOps function;Continuous integration (CI) and (more often) continuous delivery;Automated testing	1	2.0%
None of these	1	2.0%
Developer portal or other central places to find tools/services;Continuous integration (CI) and (more often) continuous delivery;Automated testing	1	2.0%
DevOps function;Continuous integration (CI) and (more often) continuous delivery;Automated testing;Observability tools	1	2.0%
DevOps function	1	2.0%
Other values (4)	4	8.0%
(Missing)	33	66.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
continuous	16	9.5%
integration	12	7.1%
ci	12	7.1%
and	12	7.1%
more	12	7.1%
often	12	7.1%
delivery;automated	12	7.1%
devops	8	4.8%
testing;observability	8	4.8%
tools	8	4.8%
Other values (23)	56	33.3%

Most occurring characters

Value	Count	Frequency (%)
t	163	9.4%
o	162	9.4%
e	159	9.2%
	151	8.7%
n	144	8.3%
i	129	7.5%
s	96	5.5%
r	86	5.0%
u	73	4.2%
a	59	3.4%
Other values (22)	509	29.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1397	80.7%
Space Separator	151	8.7%
Uppercase Letter	91	5.3%
Other Punctuation	44	2.5%
Close Punctuation	24	1.4%
Open Punctuation	24	1.4%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
t	163	11.7%
o	162	11.6%
e	159	11.4%
n	144	10.3%
i	129	9.2%
s	96	6.9%
r	86	6.2%
u	73	5.2%
a	59	4.2%
c	50	3.6%
Other values (10)	276	19.8%

Uppercase Letter

Value	Count	Frequency (%)
C	24	26.4%
O	18	19.8%
I	14	15.4%
D	14	15.4%
A	13	14.3%
M	7	7.7%
N	1	1.1%

Other Punctuation

Value	Count	Frequency (%)
;	40	90.9%
/	4	9.1%

Space Separator

Value	Count	Frequency (%)
	151	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	24	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	24	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1488	86.0%
Common	243	14.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
t	163	11.0%
o	162	10.9%
e	159	10.7%
n	144	9.7%
i	129	8.7%
s	96	6.5%
r	86	5.8%
u	73	4.9%
a	59	4.0%
c	50	3.4%
Other values (17)	367	24.7%

Common

Value	Count	Frequency (%)
	151	62.1%
;	40	16.5%
)	24	9.9%
(	24	9.9%
/	4	1.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1731	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
t	163	9.4%
o	162	9.4%
e	159	9.2%
	151	8.7%
n	144	8.3%
i	129	7.5%
s	96	5.5%
r	86	5.0%
u	73	4.2%
a	59	3.4%
Other values (22)	509	29.4%

TrueFalse_1
Boolean

HIGH CORRELATION MISSING

Distinct	2
Distinct (%)	11.8%
Missing	33
Missing (%)	66.0%
Memory size	228.0 B

True	11
False	6
(Missing)	33

Common Values (Table)
Common Values (Plot)

Value	Count	Frequency (%)
True	11	22.0%
False	6	12.0%
(Missing)	33	66.0%

TrueFalse_2
Boolean

HIGH CORRELATION MISSING

Distinct	2
Distinct (%)	11.1%
Missing	32
Missing (%)	64.0%
Memory size	228.0 B

True	11
False	7
(Missing)	32

Common Values (Table)
Common Values (Plot)

Value	Count	Frequency (%)
True	11	22.0%
False	7	14.0%
(Missing)	32	64.0%

TrueFalse_3
Boolean

HIGH CORRELATION MISSING

Distinct	2
Distinct (%)	11.1%
Missing	32
Missing (%)	64.0%
Memory size	228.0 B

True	13
False	5
(Missing)	32

Common Values (Table)
Common Values (Plot)

Value	Count	Frequency (%)
True	13	26.0%
False	5	10.0%
(Missing)	32	64.0%

SurveyLength
Categorical

HIGH CORRELATION MISSING

Distinct	3
Distinct (%)	6.4%
Missing	3
Missing (%)	6.0%
Memory size	528.0 B

Appropriate in length	37
Too long	6
Too short	4

Length

Max length	21
Median length	21
Mean length	18.319149
Min length	8

Characters and Unicode

Total characters	861
Distinct characters	15
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Too long
2nd row	Appropriate in length
3rd row	Appropriate in length
4th row	Too long
5th row	Appropriate in length

Common Values

Value	Count	Frequency (%)
Appropriate in length	37	74.0%
Too long	6	12.0%
Too short	4	8.0%
(Missing)	3	6.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
appropriate	37	28.2%
in	37	28.2%
length	37	28.2%
too	10	7.6%
long	6	4.6%
short	4	3.1%

Most occurring characters

Value	Count	Frequency (%)
p	111	12.9%
	84	9.8%
n	80	9.3%
r	78	9.1%
t	78	9.1%
i	74	8.6%
e	74	8.6%
o	67	7.8%
l	43	5.0%
g	43	5.0%
Other values (5)	129	15.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	730	84.8%
Space Separator	84	9.8%
Uppercase Letter	47	5.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
p	111	15.2%
n	80	11.0%
r	78	10.7%
t	78	10.7%
i	74	10.1%
e	74	10.1%
o	67	9.2%
l	43	5.9%
g	43	5.9%
h	41	5.6%
Other values (2)	41	5.6%

Uppercase Letter

Value	Count	Frequency (%)
A	37	78.7%
T	10	21.3%

Space Separator

Value	Count	Frequency (%)
	84	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	777	90.2%
Common	84	9.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
p	111	14.3%
n	80	10.3%
r	78	10.0%
t	78	10.0%
i	74	9.5%
e	74	9.5%
o	67	8.6%
l	43	5.5%
g	43	5.5%
h	41	5.3%
Other values (4)	88	11.3%

Common

Value	Count	Frequency (%)
	84	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	861	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
p	111	12.9%
	84	9.8%
n	80	9.3%
r	78	9.1%
t	78	9.1%
i	74	8.6%
e	74	8.6%
o	67	7.8%
l	43	5.0%
g	43	5.0%
Other values (5)	129	15.0%

SurveyEase
Categorical

HIGH CORRELATION MISSING

Distinct	3
Distinct (%)	6.2%
Missing	2
Missing (%)	4.0%
Memory size	528.0 B

Easy	35
Neither easy nor difficult	12
Difficult	1

Length

Max length	26
Median length	4
Mean length	9.6041667
Min length	4

Characters and Unicode

Total characters	461
Distinct characters	19
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	2.1%

Sample

1st row	Difficult
2nd row	Neither easy nor difficult
3rd row	Easy
4th row	Easy
5th row	Easy

Common Values

Value	Count	Frequency (%)
Easy	35	70.0%
Neither easy nor difficult	12	24.0%
Difficult	1	2.0%
(Missing)	2	4.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
easy	47	56.0%
difficult	13	15.5%
neither	12	14.3%
nor	12	14.3%

Most occurring characters

Value	Count	Frequency (%)
a	47	10.2%
s	47	10.2%
y	47	10.2%
i	38	8.2%
e	36	7.8%
	36	7.8%
E	35	7.6%
f	26	5.6%
t	25	5.4%
r	24	5.2%
Other values (9)	100	21.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	377	81.8%
Uppercase Letter	48	10.4%
Space Separator	36	7.8%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	47	12.5%
s	47	12.5%
y	47	12.5%
i	38	10.1%
e	36	9.5%
f	26	6.9%
t	25	6.6%
r	24	6.4%
c	13	3.4%
u	13	3.4%
Other values (5)	61	16.2%

Uppercase Letter

Value	Count	Frequency (%)
E	35	72.9%
N	12	25.0%
D	1	2.1%

Space Separator

Value	Count	Frequency (%)
	36	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	425	92.2%
Common	36	7.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	47	11.1%
s	47	11.1%
y	47	11.1%
i	38	8.9%
e	36	8.5%
E	35	8.2%
f	26	6.1%
t	25	5.9%
r	24	5.6%
c	13	3.1%
Other values (8)	87	20.5%

Common

Value	Count	Frequency (%)
	36	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	461	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	47	10.2%
s	47	10.2%
y	47	10.2%
i	38	8.2%
e	36	7.8%
	36	7.8%
E	35	7.6%
f	26	5.6%
t	25	5.4%
r	24	5.2%
Other values (9)	100	21.7%

ConvertedCompYearly
Real number (ℝ)

HIGH CORRELATION MISSING

Distinct	22
Distinct (%)	91.7%
Missing	26
Missing (%)	52.0%
Infinite	0
Infinite (%)	0.0%
Mean	158816.54

Minimum	5124
Maximum	1663644
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	528.0 B

Quantile statistics

Minimum	5124
5-th percentile	21459.3
Q1	51192
median	94126
Q3	130000
95-th percentile	213340.65
Maximum	1663644
Range	1658520
Interquartile range (IQR)	78808

Descriptive statistics

Standard deviation	325234.95
Coefficient of variation (CV)	2.0478657
Kurtosis	22.454284
Mean	158816.54
Median Absolute Deviation (MAD)	38374
Skewness	4.673894
Sum	3811597
Variance	1.0577777 × 10¹¹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=22)

Value	Count	Frequency (%)
130000	2	4.0%
51192	2	4.0%
97605	1	2.0%
135000	1	2.0%
5124	1	2.0%
68160	1	2.0%
83256	1	2.0%
102000	1	2.0%
1663644	1	2.0%
106960	1	2.0%
Other values (12)	12	24.0%
(Missing)	26	52.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
5124	1	2.0%
19224	1	2.0%
34126	1	2.0%
40205	1	2.0%
49056	1	2.0%
51192	2	4.0%
60307	1	2.0%
65000	1	2.0%
68160	1	2.0%
83256	1	2.0%

Value	Count	Frequency (%)
1663644	1	2.0%
215232	1	2.0%
202623	1	2.0%
194400	1	2.0%
135000	1	2.0%
130000	2	4.0%
110000	1	2.0%
106960	1	2.0%
106644	1	2.0%
102000	1	2.0%

Auto

Heatmap
Table

	ResponseId	YearsCode	YearsCodePro	CompTotal	WorkExp	ConvertedCompYearly	MainBranch	Employment	RemoteWork	CodingActivities	EdLevel	LearnCode	LearnCodeOnline	LearnCodeCoursesCert	DevType	OrgSize	PurchaseInfluence	BuyNewTool	Country	Currency	CompFreq	LanguageHaveWorkedWith	LanguageWantToWorkWith	DatabaseHaveWorkedWith	DatabaseWantToWorkWith	PlatformHaveWorkedWith	PlatformWantToWorkWith	WebframeHaveWorkedWith	WebframeWantToWorkWith	MiscTechHaveWorkedWith	MiscTechWantToWorkWith	ToolsTechHaveWorkedWith	ToolsTechWantToWorkWith	NEWCollabToolsHaveWorkedWith	NEWCollabToolsWantToWorkWith	OpSysProfessional use	OpSysPersonal use	VersionControlSystem	VCInteraction	OfficeStackAsyncHaveWorkedWith	OfficeStackAsyncWantToWorkWith	OfficeStackSyncHaveWorkedWith	OfficeStackSyncWantToWorkWith	Blockchain	NEWSOSites	SOVisitFreq	SOAccount	SOPartFreq	SOComm	Age	Gender	Trans	Sexuality	Ethnicity	Accessibility	MentalHealth	TBranch	ICorPM	Knowledge_1	Knowledge_2	Knowledge_3	Knowledge_4	Knowledge_5	Knowledge_6	Knowledge_7	Frequency_1	Frequency_2	Frequency_3	TimeSearching	TimeAnswering	Onboarding	ProfessionalTech	TrueFalse_1	TrueFalse_2	TrueFalse_3	SurveyLength	SurveyEase
ResponseId	1.000	-0.022	0.066	-0.048	-0.078	0.073	0.000	0.000	0.115	0.000	0.000	0.000	0.241	0.270	0.119	0.000	0.000	0.000	0.134	0.164	0.000	0.000	0.000	0.000	0.000	0.311	0.000	0.000	0.335	0.000	0.361	0.000	0.199	0.000	0.000	0.149	0.000	0.235	0.173	0.000	0.000	0.174	0.000	0.116	0.275	0.000	0.000	0.000	0.217	0.000	0.096	0.000	0.086	0.145	0.252	0.042	0.510	0.000	0.000	0.478	0.000	0.000	0.000	0.215	0.213	0.266	0.000	0.000	0.000	0.149	0.000	0.000	0.000	0.000	0.367	0.163	0.177
YearsCode	-0.022	1.000	0.939	0.413	0.906	0.472	0.000	0.000	0.000	0.185	0.237	0.115	0.000	0.000	0.000	0.000	0.278	0.000	0.000	0.102	0.132	1.000	0.000	0.000	0.000	0.000	0.375	0.000	0.249	0.000	0.000	0.000	0.407	0.000	0.113	0.000	0.000	0.474	0.422	0.204	0.182	0.181	0.000	0.000	0.000	0.202	0.000	0.062	0.099	0.526	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.069	0.000	0.000	0.000	0.000	0.250	0.000	0.412	0.000	0.192	0.000	0.000	0.344	0.055
YearsCodePro	0.066	0.939	1.000	0.489	0.920	0.578	0.000	0.205	0.000	0.231	0.324	0.000	0.000	0.000	0.000	0.000	0.101	0.248	0.262	0.190	0.000	1.000	0.000	0.068	0.000	0.000	0.525	1.000	1.000	0.000	0.000	0.375	0.245	0.000	0.374	0.000	0.156	0.288	0.350	0.000	0.242	0.171	0.141	0.020	0.238	0.456	0.000	0.000	0.206	0.685	0.196	1.000	0.000	0.000	0.000	0.000	0.000	0.856	0.209	0.000	0.000	0.000	0.342	0.000	0.174	0.429	0.000	0.245	0.275	0.000	0.390	0.000	0.241	0.000	0.532	0.289	0.000
CompTotal	-0.048	0.413	0.489	1.000	0.548	0.828	0.120	0.000	0.000	0.000	0.000	0.000	0.211	1.000	0.177	0.000	0.365	0.067	0.000	0.000	0.526	1.000	0.296	0.000	0.000	0.000	0.183	1.000	1.000	0.000	0.000	0.441	0.355	0.000	0.364	0.000	0.000	0.000	0.000	0.382	0.408	0.000	0.000	0.000	0.077	0.292	0.101	0.249	0.279	0.184	0.102	1.000	0.327	0.000	0.408	0.000	0.000	0.734	0.000	0.000	0.487	0.339	0.266	0.000	0.000	0.679	0.463	0.447	0.000	0.520	0.309	0.000	0.284	0.000	0.189	0.162	0.232
WorkExp	-0.078	0.906	0.920	0.548	1.000	0.572	0.000	0.000	0.146	0.000	0.372	0.559	0.000	0.816	0.395	0.000	0.000	0.501	0.000	0.000	0.000	1.000	0.577	0.000	0.000	0.000	0.707	1.000	1.000	0.333	0.000	0.577	0.456	0.098	0.446	0.227	0.455	1.000	0.000	0.000	0.246	0.000	0.000	0.232	0.000	0.000	0.000	0.000	0.122	0.483	0.000	1.000	0.144	0.000	0.000	0.000	1.000	0.211	0.000	0.000	0.000	0.298	0.218	0.000	0.000	0.254	0.000	0.000	0.000	0.221	0.310	0.000	0.000	0.000	0.549	0.407	0.320
ConvertedCompYearly	0.073	0.472	0.578	0.828	0.572	1.000	0.181	0.342	0.449	0.631	0.000	0.195	0.000	1.000	0.000	0.499	0.380	0.000	0.422	0.000	0.024	1.000	0.000	0.499	0.308	0.000	0.707	1.000	1.000	0.000	0.000	0.408	0.364	0.000	0.343	0.293	0.060	0.000	0.127	0.563	0.153	0.315	0.356	0.000	0.254	0.000	0.000	0.000	0.000	0.414	0.000	1.000	0.000	0.000	0.000	0.000	0.024	0.961	0.166	0.000	0.000	0.000	0.000	0.000	0.000	0.601	0.000	0.376	0.146	0.000	0.254	0.392	0.000	0.000	0.295	0.439	0.000
MainBranch	0.000	0.000	0.000	0.120	0.000	0.181	1.000	0.392	0.576	0.000	0.289	0.200	0.254	0.471	0.357	0.000	0.000	0.494	0.480	0.000	0.000	0.261	0.000	0.000	0.000	0.000	0.241	0.153	0.277	0.626	0.358	0.179	0.317	0.332	0.000	0.495	0.227	0.000	0.335	0.000	0.707	0.399	0.386	0.000	0.049	0.000	0.362	0.082	0.103	0.341	0.292	0.296	0.421	0.000	0.000	0.279	0.106	0.410	0.194	0.000	0.000	0.000	0.000	0.000	0.000	0.935	0.250	0.612	0.000	0.250	0.500	0.447	0.000	0.000	0.000	0.000	0.000
Employment	0.000	0.000	0.205	0.000	0.000	0.342	0.392	1.000	0.674	0.283	0.403	0.000	0.297	0.612	0.000	0.351	0.301	0.304	0.385	0.613	0.441	0.452	0.000	0.567	0.474	0.224	0.000	0.000	0.000	0.000	0.559	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.665	0.627	0.383	0.330	0.339	0.000	0.122	0.000	0.259	0.164	0.375	0.158	0.082	0.546	0.275	0.218	0.355	0.203	0.333	0.000	0.275	0.000	0.014	0.126	0.000	0.000	0.189	0.000	0.000	0.464	0.000	0.462	0.000	0.000	0.269	0.000	0.159	0.000
RemoteWork	0.115	0.000	0.000	0.000	0.146	0.449	0.576	0.674	1.000	0.000	0.390	0.132	0.283	0.149	0.214	0.473	0.212	0.563	0.237	0.367	0.000	0.000	0.246	0.131	0.000	0.324	0.000	0.000	1.000	0.000	0.213	0.000	0.000	0.000	0.000	0.135	0.000	0.000	0.000	0.000	0.000	0.519	0.545	0.396	0.000	0.209	0.172	0.000	0.119	0.367	0.383	0.514	0.398	0.259	0.000	0.234	0.262	0.000	0.000	0.497	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.653	0.000	0.453	0.000	0.000	0.000	0.000	0.000	0.201	0.000
CodingActivities	0.000	0.185	0.231	0.000	0.000	0.631	0.000	0.283	0.000	1.000	0.024	0.000	0.000	0.274	0.245	0.338	0.000	0.000	0.514	0.213	0.071	0.000	0.000	0.381	0.354	0.000	0.222	0.540	1.000	0.327	0.000	0.191	0.000	0.000	0.000	0.325	0.000	0.000	0.167	0.477	0.573	0.372	0.000	0.000	0.000	0.000	0.000	0.143	0.153	0.071	0.000	0.000	0.000	0.280	0.000	0.000	0.000	0.775	0.205	0.216	0.000	0.178	0.418	0.179	0.000	0.408	0.000	0.020	0.349	0.000	0.000	0.463	0.000	0.249	0.000	0.464	0.000
EdLevel	0.000	0.237	0.324	0.000	0.372	0.000	0.289	0.403	0.390	0.024	1.000	0.000	0.287	0.204	0.261	0.000	0.000	0.392	0.000	0.250	0.000	1.000	0.000	0.000	0.262	0.348	0.000	0.208	0.000	0.208	0.000	0.000	0.000	0.000	0.212	0.218	0.000	0.000	0.000	0.456	0.334	0.245	0.000	0.231	0.000	0.249	0.308	0.224	0.000	0.316	0.000	0.000	0.162	0.203	0.000	0.000	0.000	0.000	0.309	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.147	0.000	0.000	0.000	0.000
LearnCode	0.000	0.115	0.000	0.000	0.559	0.195	0.200	0.000	0.132	0.000	0.000	1.000	0.000	1.000	0.067	0.158	0.000	0.000	0.404	0.000	0.000	1.000	0.079	0.192	0.090	0.000	0.360	0.000	0.340	0.000	0.000	0.387	0.335	0.000	0.207	0.221	0.000	0.360	0.000	0.000	0.000	0.000	0.000	0.163	0.167	0.201	0.288	0.000	0.243	0.000	0.127	0.000	0.353	0.000	0.274	0.295	0.000	0.258	0.354	0.073	0.235	0.000	0.000	0.000	0.433	0.433	0.118	0.354	0.000	0.225	0.000	0.394	0.000	0.000	0.250	0.000	0.401
LearnCodeOnline	0.241	0.000	0.000	0.211	0.000	0.000	0.254	0.297	0.283	0.000	0.287	0.000	1.000	1.000	0.383	0.167	0.000	0.000	0.000	0.577	0.250	1.000	0.435	0.392	0.387	1.000	1.000	0.000	1.000	1.000	1.000	0.209	0.000	0.000	1.000	0.147	0.000	0.311	0.483	0.000	1.000	0.328	1.000	0.408	0.000	0.091	0.254	0.178	0.000	0.000	0.316	0.183	0.230	0.371	0.189	1.000	0.224	0.333	0.000	0.229	0.548	0.548	0.082	0.548	0.548	0.000	0.548	0.447	0.000	0.548	0.548	0.000	0.000	0.000	0.316	0.000	0.180
LearnCodeCoursesCert	0.270	0.000	0.000	1.000	0.816	1.000	0.471	0.612	0.149	0.274	0.204	1.000	1.000	1.000	1.000	0.577	0.000	0.270	0.943	0.577	0.447	1.000	1.000	0.236	0.000	0.000	0.354	0.000	1.000	1.000	0.250	1.000	0.231	0.000	0.000	0.000	0.408	1.000	0.102	1.000	1.000	0.488	0.316	0.395	0.000	0.000	0.471	0.000	0.000	0.000	0.500	1.000	0.234	0.000	1.000	0.000	0.577	1.000	0.000	0.000	0.816	0.816	0.000	0.000	0.000	0.577	0.577	0.000	0.000	0.816	0.000	1.000	0.000	0.577	1.000	0.000	0.471
DevType	0.119	0.000	0.000	0.177	0.395	0.000	0.357	0.000	0.214	0.245	0.261	0.067	0.383	1.000	1.000	0.138	0.303	0.482	0.000	0.000	0.000	1.000	0.804	0.288	0.000	0.351	0.625	0.000	1.000	0.488	0.000	0.184	0.512	0.000	0.277	0.274	0.432	0.387	0.000	0.167	0.332	0.307	0.365	0.102	0.275	0.000	0.000	0.000	0.000	0.000	0.432	0.632	0.000	0.427	0.000	0.000	0.000	0.577	0.000	0.000	0.000	0.000	0.000	0.154	0.000	0.000	0.000	0.000	0.349	0.000	0.405	0.000	0.000	0.000	0.000	0.000	0.254
OrgSize	0.000	0.000	0.000	0.000	0.000	0.499	0.000	0.351	0.473	0.338	0.000	0.158	0.167	0.577	0.138	1.000	0.460	0.000	0.159	0.000	0.363	1.000	0.000	0.055	0.471	0.000	0.000	1.000	1.000	0.239	0.312	0.320	0.000	0.181	0.000	0.000	0.000	0.000	0.000	0.194	0.189	0.000	0.284	0.210	0.279	0.000	0.000	0.000	0.199	0.000	0.592	1.000	0.561	0.295	0.866	0.333	0.000	0.000	0.440	0.000	0.360	0.298	0.363	0.000	0.000	0.398	0.469	0.000	0.369	0.394	0.000	0.716	0.000	0.000	0.000	0.000	0.000
PurchaseInfluence	0.000	0.278	0.101	0.365	0.000	0.380	0.000	0.301	0.212	0.000	0.000	0.000	0.000	0.000	0.303	0.460	1.000	0.379	0.079	0.000	0.185	1.000	0.000	0.120	0.257	0.000	0.000	1.000	1.000	0.034	0.326	0.000	0.265	0.000	0.000	0.000	0.000	0.298	0.272	0.480	0.000	0.000	0.189	0.229	0.000	0.115	0.212	0.000	0.032	0.231	0.000	1.000	0.186	0.000	0.109	0.327	0.000	0.000	0.052	0.000	0.389	0.000	0.000	0.254	0.088	0.000	0.278	0.082	0.000	0.085	0.000	0.463	0.000	0.466	0.000	0.000	0.000
BuyNewTool	0.000	0.000	0.248	0.067	0.501	0.000	0.494	0.304	0.563	0.000	0.392	0.000	0.000	0.270	0.482	0.000	0.379	1.000	0.000	0.000	0.000	1.000	0.139	0.341	0.000	0.000	0.000	0.195	0.000	0.537	0.405	0.000	0.281	0.000	0.109	0.000	0.147	0.254	0.000	0.000	0.000	0.301	0.381	0.000	0.000	0.000	0.109	0.119	0.379	0.191	0.000	0.000	0.442	0.000	0.000	0.324	0.000	0.000	0.113	0.342	0.303	0.000	0.286	0.277	0.501	0.000	0.000	0.081	0.000	0.000	0.000	0.000	0.000	0.380	0.394	0.000	0.338
Country	0.134	0.000	0.262	0.000	0.000	0.422	0.480	0.385	0.237	0.514	0.000	0.404	0.000	0.943	0.000	0.159	0.079	0.000	1.000	0.890	0.675	0.000	0.234	0.421	0.000	0.200	0.617	0.000	0.563	0.000	0.000	0.000	0.000	0.292	0.000	0.322	0.000	0.000	0.199	0.498	0.000	0.203	0.000	0.293	0.000	0.000	0.000	0.000	0.008	0.000	0.210	0.000	0.224	0.000	0.000	0.000	0.289	0.000	0.000	0.000	0.000	0.000	0.000	0.173	0.000	0.000	0.000	0.156	0.679	0.127	0.000	0.000	0.000	0.411	0.000	0.416	0.000
Currency	0.164	0.102	0.190	0.000	0.000	0.000	0.000	0.613	0.367	0.213	0.250	0.000	0.577	0.577	0.000	0.000	0.000	0.000	0.890	1.000	0.757	0.247	0.422	0.355	0.089	0.406	0.546	1.000	1.000	0.000	0.000	0.000	0.292	0.187	0.000	0.000	0.000	0.000	0.000	0.420	0.000	0.403	0.000	0.000	0.000	0.000	0.000	0.137	0.000	0.089	0.357	1.000	0.000	0.000	0.000	0.000	0.168	0.000	0.000	0.088	0.000	0.000	0.000	0.313	0.118	0.000	0.000	0.000	0.475	0.000	0.238	0.000	0.000	0.000	0.000	0.356	0.336
CompFreq	0.000	0.132	0.000	0.526	0.000	0.024	0.000	0.441	0.000	0.071	0.000	0.000	0.250	0.447	0.000	0.363	0.185	0.000	0.675	0.757	1.000	1.000	0.000	0.333	0.242	0.437	0.329	1.000	1.000	0.000	0.000	0.000	0.356	0.282	0.000	0.287	0.100	0.000	0.000	0.572	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.351	0.000	0.000	0.040	1.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.231	0.535	0.499	0.000	0.090	0.000	0.081	0.000	0.140	0.209	0.000	0.277	0.000	0.000	0.000	0.245	0.234
LanguageHaveWorkedWith	0.000	1.000	1.000	1.000	1.000	1.000	0.261	0.452	0.000	0.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	0.000	0.247	1.000	1.000	0.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	0.000	0.302	1.000	1.000	1.000	1.000	1.000	0.000	0.000	0.000	0.213	0.000	0.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	0.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	0.216	0.000
LanguageWantToWorkWith	0.000	0.000	0.000	0.296	0.577	0.000	0.000	0.000	0.246	0.000	0.000	0.079	0.435	1.000	0.804	0.000	0.000	0.139	0.234	0.422	0.000	0.000	1.000	0.312	1.000	0.849	1.000	0.000	0.000	0.808	1.000	1.000	1.000	0.000	0.000	0.000	0.412	0.309	0.000	1.000	1.000	0.312	1.000	0.186	0.309	0.192	0.000	0.000	0.158	0.000	0.316	0.224	0.397	0.259	0.229	0.303	0.196	0.267	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.365	0.516	0.365	0.000	0.447	0.000	0.000	0.000	0.258	0.258	0.000	0.126
DatabaseHaveWorkedWith	0.000	0.000	0.068	0.000	0.000	0.499	0.000	0.567	0.131	0.381	0.000	0.192	0.392	0.236	0.288	0.055	0.120	0.341	0.421	0.355	0.333	1.000	0.312	1.000	0.636	0.471	0.717	0.414	0.170	0.367	0.425	0.329	0.169	0.000	0.000	0.177	0.000	0.158	0.000	0.459	0.000	0.062	0.000	0.144	0.000	0.000	0.000	0.000	0.271	0.000	0.569	0.561	0.490	0.160	0.559	0.409	0.337	0.392	0.000	0.000	0.000	0.000	0.000	0.500	0.289	0.000	0.000	0.282	0.260	0.000	0.168	0.096	0.000	0.101	0.463	0.491	0.000
DatabaseWantToWorkWith	0.000	0.000	0.000	0.000	0.000	0.308	0.000	0.474	0.000	0.354	0.262	0.090	0.387	0.000	0.000	0.471	0.257	0.000	0.000	0.089	0.242	1.000	1.000	0.636	1.000	0.306	1.000	0.000	0.000	0.329	0.716	0.255	0.000	0.000	0.000	0.228	0.224	0.000	0.000	0.523	1.000	0.000	0.000	0.000	0.112	0.000	0.106	0.000	0.000	0.000	0.000	0.000	0.000	0.391	0.471	0.216	0.459	0.316	0.447	0.000	0.548	0.229	0.158	0.000	0.000	0.000	0.632	0.447	0.548	0.000	0.354	0.408	0.333	0.000	0.316	0.000	0.000
PlatformHaveWorkedWith	0.311	0.000	0.000	0.000	0.000	0.000	0.000	0.224	0.324	0.000	0.348	0.000	1.000	0.000	0.351	0.000	0.000	0.000	0.200	0.406	0.437	1.000	0.849	0.471	0.306	1.000	0.357	0.000	0.559	0.657	1.000	0.000	0.000	0.000	0.000	0.000	0.000	0.271	0.193	0.477	1.000	0.000	0.000	0.000	0.345	0.000	0.000	0.000	0.000	0.000	0.354	1.000	0.000	0.100	0.590	0.000	0.000	0.000	0.000	0.323	0.000	0.000	0.000	0.086	0.000	0.000	0.540	0.177	0.000	0.577	0.000	0.000	0.063	0.107	0.000	0.000	0.246
PlatformWantToWorkWith	0.000	0.375	0.525	0.183	0.707	0.707	0.241	0.000	0.000	0.222	0.000	0.360	1.000	0.354	0.625	0.000	0.000	0.000	0.617	0.546	0.329	1.000	1.000	0.717	1.000	0.357	1.000	0.000	1.000	0.000	1.000	0.395	0.391	0.000	0.326	0.565	0.317	0.160	0.000	0.186	0.000	0.606	0.519	0.000	0.498	0.327	0.000	0.282	0.000	0.000	0.594	1.000	0.000	0.374	1.000	0.000	0.000	0.632	0.000	0.289	0.000	0.000	0.000	0.289	0.000	0.000	0.000	0.289	1.000	0.000	0.354	1.000	0.000	0.000	0.632	0.334	0.000
WebframeHaveWorkedWith	0.000	0.000	1.000	1.000	1.000	1.000	0.153	0.000	0.000	0.540	0.208	0.000	0.000	0.000	0.000	1.000	1.000	0.195	0.000	1.000	1.000	1.000	0.000	0.414	0.000	0.000	0.000	1.000	0.000	0.270	0.358	0.412	0.000	0.000	0.000	0.146	0.000	0.316	0.369	1.000	1.000	0.000	0.386	0.000	0.000	0.000	0.316	0.378	0.000	0.155	0.322	0.316	0.430	0.320	0.000	0.275	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	0.322	0.000
WebframeWantToWorkWith	0.335	0.249	1.000	1.000	1.000	1.000	0.277	0.000	1.000	1.000	0.000	0.340	1.000	1.000	1.000	1.000	1.000	0.000	0.563	1.000	1.000	1.000	0.000	0.170	0.000	0.559	1.000	0.000	1.000	0.165	1.000	0.126	1.000	0.000	0.475	0.390	0.213	0.277	0.519	0.210	0.000	0.461	0.285	0.000	0.340	0.128	0.000	1.000	0.392	0.000	0.283	1.000	0.000	0.000	0.204	0.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	0.283	0.196
MiscTechHaveWorkedWith	0.000	0.000	0.000	0.000	0.333	0.000	0.626	0.000	0.000	0.327	0.208	0.000	1.000	1.000	0.488	0.239	0.034	0.537	0.000	0.000	0.000	1.000	0.808	0.367	0.329	0.657	0.000	0.270	0.165	1.000	0.555	0.438	0.381	0.659	0.000	0.465	0.430	0.000	0.000	0.261	0.258	0.108	0.000	0.000	0.279	0.371	0.626	0.000	0.000	0.000	1.000	1.000	0.000	0.000	1.000	0.000	0.000	0.447	0.000	0.000	0.000	0.408	0.373	0.000	0.000	0.548	0.480	0.351	0.000	0.333	0.000	0.335	0.000	0.000	0.000	0.326	0.438
MiscTechWantToWorkWith	0.361	0.000	0.000	0.000	0.000	0.000	0.358	0.559	0.213	0.000	0.000	0.000	1.000	0.250	0.000	0.312	0.326	0.405	0.000	0.000	0.000	1.000	1.000	0.425	0.716	1.000	1.000	0.358	1.000	0.555	1.000	0.000	0.000	1.000	0.000	0.433	0.477	0.000	0.000	0.500	1.000	0.000	0.210	0.236	0.000	0.000	0.542	0.000	0.077	0.000	1.000	1.000	0.000	0.000	1.000	0.427	0.000	1.000	0.500	0.217	0.000	0.000	0.000	0.217	0.000	0.500	0.280	0.500	0.000	0.000	0.000	0.000	0.000	0.000	0.354	0.000	0.000
ToolsTechHaveWorkedWith	0.000	0.000	0.375	0.441	0.577	0.408	0.179	0.000	0.000	0.191	0.000	0.387	0.209	1.000	0.184	0.320	0.000	0.000	0.000	0.000	0.000	1.000	1.000	0.329	0.255	0.000	0.395	0.412	0.126	0.438	0.000	1.000	0.404	0.000	0.204	0.000	0.000	0.000	0.295	0.000	0.000	0.090	0.000	0.000	0.000	0.000	0.000	0.066	0.000	0.000	0.375	0.000	0.000	0.320	0.346	0.000	0.000	0.289	0.000	0.000	0.000	0.000	0.079	0.500	0.000	0.000	0.000	0.408	0.500	0.000	0.577	1.000	1.000	0.000	0.289	0.000	0.000
ToolsTechWantToWorkWith	0.199	0.407	0.245	0.355	0.456	0.364	0.317	0.000	0.000	0.000	0.000	0.335	0.000	0.231	0.512	0.000	0.265	0.281	0.000	0.292	0.356	1.000	1.000	0.169	0.000	0.000	0.391	0.000	1.000	0.381	0.000	0.404	1.000	0.000	0.159	0.000	0.318	0.318	0.279	0.000	0.177	0.300	0.196	0.000	0.237	0.323	0.000	0.000	0.000	0.000	0.674	0.659	0.236	0.000	0.307	0.455	0.000	0.603	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.471	0.000	0.000	0.000	0.000	0.421	0.000	0.334	0.000	0.000	0.333	0.000
NEWCollabToolsHaveWorkedWith	0.000	0.000	0.000	0.000	0.098	0.000	0.332	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.181	0.000	0.000	0.292	0.187	0.282	1.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.659	1.000	0.000	0.000	1.000	0.647	0.400	0.144	0.000	0.211	0.255	0.346	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.066	0.000	0.000	0.447	0.000	0.104	0.365	0.220	0.041	0.000	0.186	0.242	0.000	0.000	0.447	0.375	0.226	0.000	0.401	0.000	0.000	0.000	0.028	0.000	0.000	0.264
NEWCollabToolsWantToWorkWith	0.000	0.113	0.374	0.364	0.446	0.343	0.000	0.000	0.000	0.000	0.212	0.207	1.000	0.000	0.277	0.000	0.000	0.109	0.000	0.000	0.000	1.000	0.000	0.000	0.000	0.000	0.326	0.000	0.475	0.000	0.000	0.204	0.159	0.647	1.000	0.256	0.386	0.142	0.088	0.000	0.000	0.000	0.000	0.000	0.413	0.000	0.000	0.084	0.000	0.173	0.000	0.000	0.000	0.000	0.203	0.000	0.369	0.522	0.304	0.000	0.267	0.363	0.217	0.000	0.275	0.451	0.226	0.191	0.000	0.361	0.000	0.000	0.426	0.209	0.000	0.000	0.324
OpSysProfessional use	0.149	0.000	0.000	0.000	0.227	0.293	0.495	0.000	0.135	0.325	0.218	0.221	0.147	0.000	0.274	0.000	0.000	0.000	0.322	0.000	0.287	1.000	0.000	0.177	0.228	0.000	0.565	0.146	0.390	0.465	0.433	0.000	0.000	0.400	0.256	1.000	0.425	0.000	0.488	0.284	0.288	0.165	0.190	0.000	0.000	0.275	0.000	0.155	0.000	0.000	0.000	0.269	0.000	0.000	0.212	0.000	0.000	0.832	0.245	0.000	0.000	0.343	0.385	0.000	0.038	0.483	0.000	0.470	0.298	0.270	0.000	0.285	0.000	0.000	0.391	0.000	0.000
OpSysPersonal use	0.000	0.000	0.156	0.000	0.455	0.060	0.227	0.000	0.000	0.000	0.000	0.000	0.000	0.408	0.432	0.000	0.000	0.147	0.000	0.000	0.100	0.000	0.412	0.000	0.224	0.000	0.317	0.000	0.213	0.430	0.477	0.000	0.318	0.144	0.386	0.425	1.000	0.224	0.000	0.000	0.290	0.000	0.000	0.080	0.299	0.000	0.000	0.236	0.399	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.473	0.894	0.225	0.000	0.146	0.493	0.457	0.000	0.000	0.486	0.139	0.208	0.000	0.362	0.459	0.000	0.057	0.000	0.000	0.000	0.632
VersionControlSystem	0.235	0.474	0.288	0.000	1.000	0.000	0.000	0.000	0.000	0.000	0.000	0.360	0.311	1.000	0.387	0.000	0.298	0.254	0.000	0.000	0.000	0.302	0.309	0.158	0.000	0.271	0.160	0.316	0.277	0.000	0.000	0.000	0.318	0.000	0.142	0.000	0.224	1.000	0.448	0.442	0.000	0.000	0.440	0.113	0.150	0.300	0.000	0.104	0.000	0.196	0.000	0.000	0.000	0.000	0.000	0.440	0.224	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	0.207	0.000
VCInteraction	0.173	0.422	0.350	0.000	0.000	0.127	0.335	0.000	0.000	0.167	0.000	0.000	0.483	0.102	0.000	0.000	0.272	0.000	0.199	0.000	0.000	1.000	0.000	0.000	0.000	0.193	0.000	0.369	0.519	0.000	0.000	0.295	0.279	0.211	0.088	0.488	0.000	0.448	1.000	0.321	0.155	0.394	0.153	0.000	0.000	0.000	0.194	0.000	0.061	0.225	0.474	0.610	0.000	0.000	0.344	0.000	0.000	0.775	0.125	0.384	0.000	0.000	0.000	0.299	0.105	0.469	0.201	0.441	0.000	0.208	0.129	0.417	0.069	0.369	0.309	0.000	0.000
OfficeStackAsyncHaveWorkedWith	0.000	0.204	0.000	0.382	0.000	0.563	0.000	0.665	0.000	0.477	0.456	0.000	0.000	1.000	0.167	0.194	0.480	0.000	0.498	0.420	0.572	1.000	1.000	0.459	0.523	0.477	0.186	1.000	0.210	0.261	0.500	0.000	0.000	0.255	0.000	0.284	0.000	0.442	0.321	1.000	0.594	0.000	0.000	0.000	0.000	0.315	0.000	0.137	0.000	0.245	0.000	0.000	0.271	0.000	0.232	0.410	0.127	0.000	0.000	0.364	0.362	0.000	0.289	0.398	0.000	0.000	0.171	0.000	0.402	0.000	0.000	0.612	0.379	0.620	0.000	0.440	0.000
OfficeStackAsyncWantToWorkWith	0.000	0.182	0.242	0.408	0.246	0.153	0.707	0.627	0.000	0.573	0.334	0.000	1.000	1.000	0.332	0.189	0.000	0.000	0.000	0.000	0.000	1.000	1.000	0.000	1.000	1.000	0.000	1.000	0.000	0.258	1.000	0.000	0.177	0.346	0.000	0.288	0.290	0.000	0.155	0.594	1.000	0.082	0.000	0.323	0.000	0.000	0.131	0.000	0.103	0.294	0.000	1.000	0.178	0.000	0.000	0.000	0.000	0.500	0.535	0.231	0.000	0.401	0.491	0.000	0.000	0.231	0.000	0.246	0.000	0.000	0.293	0.378	0.378	0.000	0.125	0.580	0.000
OfficeStackSyncHaveWorkedWith	0.174	0.181	0.171	0.000	0.000	0.315	0.399	0.383	0.519	0.372	0.245	0.000	0.328	0.488	0.307	0.000	0.000	0.301	0.203	0.403	0.000	1.000	0.312	0.062	0.000	0.000	0.606	0.000	0.461	0.108	0.000	0.090	0.300	0.000	0.000	0.165	0.000	0.000	0.394	0.000	0.082	1.000	0.660	0.192	0.115	0.318	0.213	0.171	0.054	0.199	0.690	0.828	0.261	0.277	0.000	0.185	0.000	0.707	0.000	0.294	0.096	0.000	0.000	0.000	0.430	0.092	0.000	0.000	0.000	0.000	0.287	0.382	0.102	0.000	0.000	0.404	0.247
OfficeStackSyncWantToWorkWith	0.000	0.000	0.141	0.000	0.000	0.356	0.386	0.330	0.545	0.000	0.000	0.000	1.000	0.316	0.365	0.284	0.189	0.381	0.000	0.000	0.000	1.000	1.000	0.000	0.000	0.000	0.519	0.386	0.285	0.000	0.210	0.000	0.196	0.000	0.000	0.190	0.000	0.440	0.153	0.000	0.000	0.660	1.000	0.160	0.131	0.000	0.000	0.090	0.000	0.426	0.709	0.866	0.368	0.556	0.243	0.281	0.000	0.000	0.000	0.361	0.564	0.365	0.000	0.000	0.472	0.000	0.212	0.000	0.435	0.170	0.507	0.000	0.613	0.000	0.000	0.000	0.075
Blockchain	0.116	0.000	0.020	0.000	0.232	0.000	0.000	0.339	0.396	0.000	0.231	0.163	0.408	0.395	0.102	0.210	0.229	0.000	0.293	0.000	0.000	0.000	0.186	0.144	0.000	0.000	0.000	0.000	0.000	0.000	0.236	0.000	0.000	0.000	0.000	0.000	0.080	0.113	0.000	0.000	0.323	0.192	0.160	1.000	0.000	0.213	0.301	0.061	0.000	0.161	0.164	0.162	0.218	0.202	0.000	0.201	0.306	0.548	0.000	0.000	0.321	0.315	0.253	0.000	0.000	0.204	0.000	0.338	0.170	0.000	0.000	0.405	0.000	0.000	0.569	0.000	0.000
NEWSOSites	0.275	0.000	0.238	0.077	0.000	0.254	0.049	0.000	0.000	0.000	0.000	0.167	0.000	0.000	0.275	0.279	0.000	0.000	0.000	0.000	0.000	0.000	0.309	0.000	0.112	0.345	0.498	0.000	0.340	0.279	0.000	0.000	0.237	0.000	0.413	0.000	0.299	0.150	0.000	0.000	0.000	0.115	0.131	0.000	1.000	0.203	0.000	0.331	0.353	0.000	0.107	0.000	0.000	0.000	0.169	0.285	0.216	0.000	0.318	0.000	0.000	0.000	0.000	0.000	0.000	0.565	0.000	0.000	0.319	0.465	0.000	0.335	0.482	0.000	0.000	0.122	0.191
SOVisitFreq	0.000	0.202	0.456	0.292	0.000	0.000	0.000	0.122	0.209	0.000	0.249	0.201	0.091	0.000	0.000	0.000	0.115	0.000	0.000	0.000	0.000	0.000	0.192	0.000	0.000	0.000	0.327	0.000	0.128	0.371	0.000	0.000	0.323	0.000	0.000	0.275	0.000	0.300	0.000	0.315	0.000	0.318	0.000	0.213	0.203	1.000	0.332	0.447	0.350	0.098	0.000	0.000	0.071	0.000	0.313	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.062	0.058	0.000	0.075	0.327	0.094	0.104	0.000	0.000	0.000	0.337	0.268	0.000
SOAccount	0.000	0.000	0.000	0.101	0.000	0.000	0.362	0.000	0.172	0.000	0.308	0.288	0.254	0.471	0.000	0.000	0.212	0.109	0.000	0.000	0.000	0.213	0.000	0.000	0.106	0.000	0.000	0.316	0.000	0.626	0.542	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.194	0.000	0.131	0.213	0.000	0.301	0.000	0.332	1.000	1.000	0.298	0.000	0.420	0.174	0.398	0.260	0.000	0.338	0.105	0.000	0.226	0.000	0.694	0.077	0.228	0.000	0.000	0.000	0.701	0.000	0.000	0.206	0.000	0.463	0.000	0.208	0.000	0.000	0.000
SOPartFreq	0.000	0.062	0.000	0.249	0.000	0.000	0.082	0.259	0.000	0.143	0.224	0.000	0.178	0.000	0.000	0.000	0.000	0.119	0.000	0.137	0.351	0.000	0.000	0.000	0.000	0.000	0.282	0.378	1.000	0.000	0.000	0.066	0.000	0.000	0.084	0.155	0.236	0.104	0.000	0.137	0.000	0.171	0.090	0.061	0.331	0.447	1.000	1.000	0.354	0.000	0.020	0.000	0.102	0.000	0.000	0.000	0.000	0.000	0.276	0.000	0.491	0.178	0.371	0.247	0.274	0.000	0.000	0.000	0.498	0.000	0.529	0.232	0.542	0.000	0.139	0.000	0.137
SOComm	0.217	0.099	0.206	0.279	0.122	0.000	0.103	0.164	0.119	0.153	0.000	0.243	0.000	0.000	0.000	0.199	0.032	0.379	0.008	0.000	0.000	0.000	0.158	0.271	0.000	0.000	0.000	0.000	0.392	0.000	0.077	0.000	0.000	0.000	0.000	0.000	0.399	0.000	0.061	0.000	0.103	0.054	0.000	0.000	0.353	0.350	0.298	0.354	1.000	0.009	0.193	0.000	0.399	0.000	0.000	0.153	0.000	0.000	0.305	0.440	0.163	0.000	0.000	0.000	0.164	0.586	0.208	0.000	0.260	0.389	0.000	0.226	0.000	0.377	0.000	0.170	0.708
Age	0.000	0.526	0.685	0.184	0.483	0.414	0.341	0.375	0.367	0.071	0.316	0.000	0.000	0.000	0.000	0.000	0.231	0.191	0.000	0.089	0.000	1.000	0.000	0.000	0.000	0.000	0.000	0.155	0.000	0.000	0.000	0.000	0.000	0.000	0.173	0.000	0.000	0.196	0.225	0.245	0.294	0.199	0.426	0.161	0.000	0.098	0.000	0.000	0.009	1.000	0.000	0.087	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.099	0.280	0.104	0.322	0.000	0.440	0.000	0.000	0.000	0.000	0.000	0.163	0.000	0.000	0.000	0.740	0.000	0.000
Gender	0.096	0.000	0.196	0.102	0.000	0.000	0.292	0.158	0.383	0.000	0.000	0.127	0.316	0.500	0.432	0.592	0.000	0.000	0.210	0.357	0.040	1.000	0.316	0.569	0.000	0.354	0.594	0.322	0.283	1.000	1.000	0.375	0.674	0.000	0.000	0.000	0.000	0.000	0.474	0.000	0.000	0.690	0.709	0.164	0.107	0.000	0.420	0.020	0.193	0.000	1.000	0.852	0.739	0.572	0.445	0.331	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.158	0.000	0.395	0.183	0.000	0.446	0.622	0.389	0.000	0.000	0.000	0.000	0.000	0.000
Trans	0.000	0.000	1.000	1.000	1.000	1.000	0.296	0.082	0.514	0.000	0.000	0.000	0.183	1.000	0.632	1.000	1.000	0.000	0.000	1.000	1.000	1.000	0.224	0.561	0.000	1.000	1.000	0.316	1.000	1.000	1.000	0.000	0.659	0.066	0.000	0.269	0.000	0.000	0.610	0.000	1.000	0.828	0.866	0.162	0.000	0.000	0.174	0.000	0.000	0.087	0.852	1.000	0.608	0.721	0.455	0.632	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	0.078	0.000
Sexuality	0.086	0.000	0.000	0.327	0.144	0.000	0.421	0.546	0.398	0.000	0.162	0.353	0.230	0.234	0.000	0.561	0.186	0.442	0.224	0.000	0.000	1.000	0.397	0.490	0.000	0.000	0.000	0.430	0.000	0.000	0.000	0.000	0.236	0.000	0.000	0.000	0.000	0.000	0.000	0.271	0.178	0.261	0.368	0.218	0.000	0.071	0.398	0.102	0.399	0.000	0.739	0.608	1.000	0.399	0.666	0.492	0.121	0.000	0.238	0.000	0.000	0.000	0.000	0.000	0.000	0.729	0.000	0.000	0.000	0.583	0.000	0.463	0.132	0.078	0.000	0.000	0.000
Ethnicity	0.145	0.000	0.000	0.000	0.000	0.000	0.000	0.275	0.259	0.280	0.203	0.000	0.371	0.000	0.427	0.295	0.000	0.000	0.000	0.000	0.000	1.000	0.259	0.160	0.391	0.100	0.374	0.320	0.000	0.000	0.000	0.320	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.277	0.556	0.202	0.000	0.000	0.260	0.000	0.000	0.000	0.572	0.721	0.399	1.000	0.174	0.302	0.000	0.000	0.000	0.161	0.000	0.000	0.000	0.368	0.000	0.000	0.000	0.000	0.088	0.000	0.000	0.000	0.257	0.127	0.000	0.000	0.000
Accessibility	0.252	0.000	0.000	0.408	0.000	0.000	0.000	0.218	0.000	0.000	0.000	0.274	0.189	1.000	0.000	0.866	0.109	0.000	0.000	0.000	0.000	1.000	0.229	0.559	0.471	0.590	1.000	0.000	0.204	1.000	1.000	0.346	0.307	0.447	0.203	0.212	0.000	0.000	0.344	0.232	0.000	0.000	0.243	0.000	0.169	0.313	0.000	0.000	0.000	0.000	0.445	0.455	0.666	0.174	1.000	0.700	0.000	0.000	0.000	0.177	0.000	0.000	0.000	0.000	0.000	0.935	0.250	0.194	0.354	0.901	0.000	0.447	0.000	0.000	0.000	0.000	0.000
MentalHealth	0.042	0.000	0.000	0.000	0.000	0.000	0.279	0.355	0.234	0.000	0.000	0.295	1.000	0.000	0.000	0.333	0.327	0.324	0.000	0.000	0.000	1.000	0.303	0.409	0.216	0.000	0.000	0.275	0.000	0.000	0.427	0.000	0.455	0.000	0.000	0.000	0.000	0.440	0.000	0.410	0.000	0.185	0.281	0.201	0.285	0.000	0.338	0.000	0.153	0.000	0.331	0.632	0.492	0.302	0.700	1.000	0.000	0.886	0.000	0.000	0.245	0.000	0.000	0.000	0.161	0.732	0.206	0.342	0.172	0.385	0.298	0.411	0.325	0.000	0.000	0.172	0.193
TBranch	0.510	0.000	0.000	0.000	1.000	0.024	0.106	0.203	0.262	0.000	0.000	0.000	0.224	0.577	0.000	0.000	0.000	0.000	0.289	0.168	0.000	0.000	0.196	0.337	0.459	0.000	0.000	1.000	1.000	0.000	0.000	0.000	0.000	0.104	0.369	0.000	0.473	0.224	0.000	0.127	0.000	0.000	0.000	0.306	0.216	0.000	0.105	0.000	0.000	0.000	0.000	1.000	0.121	0.000	0.000	0.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	0.000	0.233
ICorPM	0.000	0.000	0.856	0.734	0.211	0.961	0.410	0.333	0.000	0.775	0.000	0.258	0.333	1.000	0.577	0.000	0.000	0.000	0.000	0.000	0.000	1.000	0.267	0.392	0.316	0.000	0.632	1.000	1.000	0.447	1.000	0.289	0.603	0.365	0.522	0.832	0.894	1.000	0.775	0.000	0.500	0.707	0.000	0.548	0.000	0.000	0.000	0.000	0.000	0.000	0.000	1.000	0.000	0.000	0.000	0.886	1.000	1.000	0.289	0.000	0.000	0.000	0.000	0.000	0.000	0.931	0.211	0.606	0.000	0.211	0.894	0.378	0.000	0.000	0.000	0.606	0.000
Knowledge_1	0.000	0.000	0.209	0.000	0.000	0.166	0.194	0.000	0.000	0.205	0.309	0.354	0.000	0.000	0.000	0.440	0.052	0.113	0.000	0.000	0.000	1.000	0.000	0.000	0.447	0.000	0.000	1.000	1.000	0.000	0.500	0.000	0.000	0.220	0.304	0.245	0.225	1.000	0.125	0.000	0.535	0.000	0.000	0.000	0.318	0.000	0.226	0.276	0.305	0.000	0.000	1.000	0.238	0.000	0.000	0.000	1.000	0.289	1.000	0.000	0.122	0.000	0.280	0.000	0.000	0.327	0.000	0.000	0.134	0.000	0.038	0.000	0.000	0.466	0.000	0.000	0.000
Knowledge_2	0.478	0.000	0.000	0.000	0.000	0.000	0.000	0.275	0.497	0.216	0.000	0.073	0.229	0.000	0.000	0.000	0.000	0.342	0.000	0.088	0.000	1.000	0.000	0.000	0.000	0.323	0.289	1.000	1.000	0.000	0.217	0.000	0.000	0.041	0.000	0.000	0.000	1.000	0.384	0.364	0.231	0.294	0.361	0.000	0.000	0.000	0.000	0.000	0.440	0.099	0.000	1.000	0.000	0.161	0.177	0.000	1.000	0.000	0.000	1.000	0.258	0.000	0.000	0.359	0.507	0.000	0.173	0.301	0.000	0.324	0.000	0.234	0.229	0.513	0.000	0.000	0.000
Knowledge_3	0.000	0.000	0.000	0.487	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.235	0.548	0.816	0.000	0.360	0.389	0.303	0.000	0.000	0.231	1.000	0.000	0.000	0.548	0.000	0.000	1.000	1.000	0.000	0.000	0.000	0.000	0.000	0.267	0.000	0.146	1.000	0.000	0.362	0.000	0.096	0.564	0.321	0.000	0.000	0.694	0.491	0.163	0.280	0.000	1.000	0.000	0.000	0.000	0.245	1.000	0.000	0.122	0.258	1.000	0.499	0.469	0.000	0.611	0.000	0.397	0.000	0.000	0.316	0.000	0.349	0.000	0.290	0.259	0.000	0.000
Knowledge_4	0.000	0.000	0.000	0.339	0.298	0.000	0.000	0.014	0.000	0.178	0.000	0.000	0.548	0.816	0.000	0.298	0.000	0.000	0.000	0.000	0.535	1.000	0.000	0.000	0.229	0.000	0.000	1.000	1.000	0.408	0.000	0.000	0.000	0.186	0.363	0.343	0.493	1.000	0.000	0.000	0.401	0.000	0.365	0.315	0.000	0.000	0.077	0.178	0.000	0.104	0.000	1.000	0.000	0.000	0.000	0.000	1.000	0.000	0.000	0.000	0.499	1.000	0.726	0.000	0.143	0.000	0.000	0.000	0.168	0.123	0.126	0.000	0.000	0.135	0.000	0.000	0.000
Knowledge_5	0.000	0.000	0.342	0.266	0.218	0.000	0.000	0.126	0.000	0.418	0.000	0.000	0.082	0.000	0.000	0.363	0.000	0.286	0.000	0.000	0.499	1.000	0.000	0.000	0.158	0.000	0.000	1.000	1.000	0.373	0.000	0.079	0.000	0.242	0.217	0.385	0.457	1.000	0.000	0.289	0.491	0.000	0.000	0.253	0.000	0.000	0.228	0.371	0.000	0.322	0.000	1.000	0.000	0.000	0.000	0.000	1.000	0.000	0.280	0.000	0.469	0.726	1.000	0.000	0.000	0.399	0.000	0.000	0.014	0.139	0.000	0.000	0.206	0.438	0.203	0.000	0.000
Knowledge_6	0.215	0.069	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.179	0.000	0.000	0.548	0.000	0.154	0.000	0.254	0.277	0.173	0.313	0.000	1.000	0.000	0.500	0.000	0.086	0.289	1.000	1.000	0.000	0.217	0.500	0.000	0.000	0.000	0.000	0.000	1.000	0.299	0.398	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.247	0.000	0.000	0.158	1.000	0.000	0.368	0.000	0.000	1.000	0.000	0.000	0.359	0.000	0.000	0.000	1.000	0.046	0.000	0.000	0.000	0.000	0.000	0.238	0.325	0.000	0.000	0.000	0.000	0.462
Knowledge_7	0.213	0.000	0.174	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.433	0.548	0.000	0.000	0.000	0.088	0.501	0.000	0.118	0.090	1.000	0.000	0.289	0.000	0.000	0.000	1.000	1.000	0.000	0.000	0.000	0.000	0.000	0.275	0.038	0.000	1.000	0.105	0.000	0.000	0.430	0.472	0.000	0.000	0.062	0.000	0.274	0.164	0.440	0.000	1.000	0.000	0.000	0.000	0.161	1.000	0.000	0.000	0.507	0.611	0.143	0.000	0.046	1.000	0.000	0.000	0.000	0.000	0.222	0.000	0.389	0.000	0.075	0.569	0.000	0.000
Frequency_1	0.266	0.000	0.429	0.679	0.254	0.601	0.935	0.189	0.000	0.408	0.000	0.433	0.000	0.577	0.000	0.398	0.000	0.000	0.000	0.000	0.000	1.000	0.365	0.000	0.000	0.000	0.000	1.000	1.000	0.548	0.500	0.000	0.471	0.447	0.451	0.483	0.486	1.000	0.469	0.000	0.231	0.092	0.000	0.204	0.565	0.058	0.000	0.000	0.586	0.000	0.395	1.000	0.729	0.000	0.935	0.732	1.000	0.931	0.327	0.000	0.000	0.000	0.399	0.000	0.000	1.000	0.298	0.397	0.000	0.534	0.000	0.480	0.000	0.000	0.245	0.297	0.000
Frequency_2	0.000	0.000	0.000	0.463	0.000	0.000	0.250	0.000	0.000	0.000	0.000	0.118	0.548	0.577	0.000	0.469	0.278	0.000	0.000	0.000	0.081	1.000	0.516	0.000	0.632	0.540	0.000	1.000	1.000	0.480	0.280	0.000	0.000	0.375	0.226	0.000	0.139	1.000	0.201	0.171	0.000	0.000	0.212	0.000	0.000	0.000	0.701	0.000	0.208	0.000	0.183	1.000	0.000	0.000	0.250	0.206	1.000	0.211	0.000	0.173	0.397	0.000	0.000	0.000	0.000	0.298	1.000	0.380	0.000	0.368	0.153	0.222	0.000	0.000	0.107	0.476	0.000
Frequency_3	0.000	0.000	0.245	0.447	0.000	0.376	0.612	0.000	0.653	0.020	0.000	0.354	0.447	0.000	0.000	0.000	0.082	0.081	0.156	0.000	0.000	1.000	0.365	0.282	0.447	0.177	0.289	1.000	1.000	0.351	0.500	0.408	0.000	0.226	0.191	0.470	0.208	1.000	0.441	0.000	0.246	0.000	0.000	0.338	0.000	0.075	0.000	0.000	0.000	0.000	0.000	1.000	0.000	0.000	0.194	0.342	1.000	0.606	0.000	0.301	0.000	0.000	0.000	0.000	0.000	0.397	0.380	1.000	0.097	0.629	0.000	0.291	0.000	0.000	0.544	0.000	0.000
TimeSearching	0.000	0.250	0.275	0.000	0.000	0.146	0.000	0.464	0.000	0.349	0.000	0.000	0.000	0.000	0.349	0.369	0.000	0.000	0.679	0.475	0.140	1.000	0.000	0.260	0.548	0.000	1.000	1.000	1.000	0.000	0.000	0.500	0.000	0.000	0.000	0.298	0.000	1.000	0.000	0.402	0.000	0.000	0.435	0.170	0.319	0.327	0.000	0.498	0.260	0.000	0.446	1.000	0.000	0.088	0.354	0.172	1.000	0.000	0.134	0.000	0.000	0.168	0.014	0.000	0.000	0.000	0.000	0.097	1.000	0.000	0.608	0.000	0.366	0.000	0.245	0.444	0.000
TimeAnswering	0.149	0.000	0.000	0.520	0.221	0.000	0.250	0.000	0.453	0.000	0.000	0.225	0.548	0.816	0.000	0.394	0.085	0.000	0.127	0.000	0.209	1.000	0.447	0.000	0.000	0.577	0.000	1.000	1.000	0.333	0.000	0.000	0.000	0.401	0.361	0.270	0.362	1.000	0.208	0.000	0.000	0.000	0.170	0.000	0.465	0.094	0.206	0.000	0.389	0.000	0.622	1.000	0.583	0.000	0.901	0.385	1.000	0.211	0.000	0.324	0.316	0.123	0.139	0.000	0.222	0.534	0.368	0.629	0.000	1.000	0.000	0.000	0.233	0.297	0.000	0.000	0.000
Onboarding	0.000	0.412	0.390	0.309	0.310	0.254	0.500	0.462	0.000	0.000	0.000	0.000	0.548	0.000	0.405	0.000	0.000	0.000	0.000	0.238	0.000	1.000	0.000	0.168	0.354	0.000	0.354	1.000	1.000	0.000	0.000	0.577	0.421	0.000	0.000	0.000	0.459	1.000	0.129	0.000	0.293	0.287	0.507	0.000	0.000	0.104	0.000	0.529	0.000	0.163	0.389	1.000	0.000	0.000	0.000	0.298	1.000	0.894	0.038	0.000	0.000	0.126	0.000	0.238	0.000	0.000	0.153	0.000	0.608	0.000	1.000	0.000	0.501	0.000	0.277	0.479	0.099
ProfessionalTech	0.000	0.000	0.000	0.000	0.000	0.392	0.447	0.000	0.000	0.463	0.000	0.394	0.000	1.000	0.000	0.716	0.463	0.000	0.000	0.000	0.277	1.000	0.000	0.096	0.408	0.000	1.000	1.000	1.000	0.335	0.000	1.000	0.000	0.000	0.000	0.285	0.000	1.000	0.417	0.612	0.378	0.382	0.000	0.405	0.335	0.000	0.463	0.232	0.226	0.000	0.000	1.000	0.463	0.000	0.447	0.411	1.000	0.378	0.000	0.234	0.349	0.000	0.000	0.325	0.389	0.480	0.222	0.291	0.000	0.000	0.000	1.000	0.000	0.165	0.000	0.000	0.447
TrueFalse_1	0.000	0.192	0.241	0.284	0.000	0.000	0.000	0.000	0.000	0.000	0.147	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	1.000	0.000	0.000	0.333	0.063	0.000	1.000	1.000	0.000	0.000	1.000	0.334	0.000	0.426	0.000	0.057	1.000	0.069	0.379	0.378	0.102	0.613	0.000	0.482	0.000	0.000	0.542	0.000	0.000	0.000	1.000	0.132	0.257	0.000	0.325	1.000	0.000	0.000	0.229	0.000	0.000	0.206	0.000	0.000	0.000	0.000	0.000	0.366	0.233	0.501	0.000	1.000	0.000	0.000	0.000	0.000
TrueFalse_2	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.269	0.000	0.249	0.000	0.000	0.000	0.577	0.000	0.000	0.466	0.380	0.411	0.000	0.000	1.000	0.258	0.101	0.000	0.107	0.000	1.000	1.000	0.000	0.000	0.000	0.000	0.028	0.209	0.000	0.000	1.000	0.369	0.620	0.000	0.000	0.000	0.000	0.000	0.000	0.208	0.000	0.377	0.000	0.000	1.000	0.078	0.127	0.000	0.000	1.000	0.000	0.466	0.513	0.290	0.135	0.438	0.000	0.075	0.000	0.000	0.000	0.000	0.297	0.000	0.165	0.000	1.000	0.000	0.000	0.000
TrueFalse_3	0.367	0.000	0.532	0.189	0.549	0.295	0.000	0.000	0.000	0.000	0.000	0.250	0.316	1.000	0.000	0.000	0.000	0.394	0.000	0.000	0.000	1.000	0.258	0.463	0.316	0.000	0.632	1.000	1.000	0.000	0.354	0.289	0.000	0.000	0.000	0.391	0.000	1.000	0.309	0.000	0.125	0.000	0.000	0.569	0.000	0.337	0.000	0.139	0.000	0.740	0.000	1.000	0.000	0.000	0.000	0.000	1.000	0.000	0.000	0.000	0.259	0.000	0.203	0.000	0.569	0.245	0.107	0.544	0.245	0.000	0.277	0.000	0.000	0.000	1.000	0.476	0.000
SurveyLength	0.163	0.344	0.289	0.162	0.407	0.439	0.000	0.159	0.201	0.464	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.416	0.356	0.245	0.216	0.000	0.491	0.000	0.000	0.334	0.322	0.283	0.326	0.000	0.000	0.333	0.000	0.000	0.000	0.000	0.207	0.000	0.440	0.580	0.404	0.000	0.000	0.122	0.268	0.000	0.000	0.170	0.000	0.000	0.078	0.000	0.000	0.000	0.172	0.000	0.606	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.297	0.476	0.000	0.444	0.000	0.479	0.000	0.000	0.000	0.476	1.000	0.181
SurveyEase	0.177	0.055	0.000	0.232	0.320	0.000	0.000	0.000	0.000	0.000	0.000	0.401	0.180	0.471	0.254	0.000	0.000	0.338	0.000	0.336	0.234	0.000	0.126	0.000	0.000	0.246	0.000	0.000	0.196	0.438	0.000	0.000	0.000	0.264	0.324	0.000	0.632	0.000	0.000	0.000	0.000	0.247	0.075	0.000	0.191	0.000	0.000	0.137	0.708	0.000	0.000	0.000	0.000	0.000	0.000	0.193	0.233	0.000	0.000	0.000	0.000	0.000	0.000	0.462	0.000	0.000	0.000	0.000	0.000	0.000	0.099	0.447	0.000	0.000	0.000	0.181	1.000

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

First rows
Last rows

	ResponseId	MainBranch	Employment	RemoteWork	CodingActivities	EdLevel	LearnCode	LearnCodeOnline	LearnCodeCoursesCert	YearsCode	YearsCodePro	DevType	OrgSize	PurchaseInfluence	BuyNewTool	Country	Currency	CompTotal	CompFreq	LanguageHaveWorkedWith	LanguageWantToWorkWith	DatabaseHaveWorkedWith	DatabaseWantToWorkWith	PlatformHaveWorkedWith	PlatformWantToWorkWith	WebframeHaveWorkedWith	WebframeWantToWorkWith	MiscTechHaveWorkedWith	MiscTechWantToWorkWith	ToolsTechHaveWorkedWith	ToolsTechWantToWorkWith	NEWCollabToolsHaveWorkedWith	NEWCollabToolsWantToWorkWith	OpSysProfessional use	OpSysPersonal use	VersionControlSystem	VCInteraction	VCHostingPersonal use	VCHostingProfessional use	OfficeStackAsyncHaveWorkedWith	OfficeStackAsyncWantToWorkWith	OfficeStackSyncHaveWorkedWith	OfficeStackSyncWantToWorkWith	Blockchain	NEWSOSites	SOVisitFreq	SOAccount	SOPartFreq	SOComm	Age	Gender	Trans	Sexuality	Ethnicity	Accessibility	MentalHealth	TBranch	ICorPM	WorkExp	Knowledge_1	Knowledge_2	Knowledge_3	Knowledge_4	Knowledge_5	Knowledge_6	Knowledge_7	Frequency_1	Frequency_2	Frequency_3	TimeSearching	TimeAnswering	Onboarding	ProfessionalTech	TrueFalse_1	TrueFalse_2	TrueFalse_3	SurveyLength	SurveyEase	ConvertedCompYearly
0	1	None of these	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1	2	I am a developer by profession	Employed, full-time	Fully remote	Hobby;Contribute to open-source projects	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Canada	CAD\tCanadian dollar	NaN	NaN	JavaScript;TypeScript	Rust;TypeScript	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	macOS	Windows Subsystem for Linux (WSL)	Git	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Very unfavorable	Collectives on Stack Overflow;Stack Overflow for Teams (private knowledge sharing & collaboration platform for companies);Stack Overflow;Stack Exchange	Daily or almost daily	Yes	Daily or almost daily	Not sure	NaN	NaN	NaN	NaN	NaN	NaN	NaN	No	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Too long	Difficult	NaN
2	3	I am not primarily a developer, but I write code sometimes as part of my work	Employed, full-time	Hybrid (some remote, some in-person)	Hobby	Master’s degree (M.A., M.S., M.Eng., MBA, etc.)	Books / Physical media;Friend or family member;Other online resources (e.g., videos, blogs, forum);School (i.e., University, College, etc)	Technical documentation;Blogs;Programming Games;Written Tutorials;Stack Overflow	NaN	14.0	5.0	Data scientist or machine learning specialist;Developer, front-end;Engineer, data;Engineer, site reliability	20 to 99 employees	I have some influence	NaN	United Kingdom of Great Britain and Northern Ireland	GBP\tPound sterling	32000.0	Yearly	C#;C++;HTML/CSS;JavaScript;Python	C#;C++;HTML/CSS;JavaScript;TypeScript	Microsoft SQL Server	Microsoft SQL Server	NaN	NaN	Angular.js	Angular;Angular.js	Pandas	.NET	NaN	NaN	Notepad++;Visual Studio	Notepad++;Visual Studio	Windows	Windows	Git	Code editor	NaN	NaN	NaN	NaN	Microsoft Teams	Microsoft Teams	Very unfavorable	Collectives on Stack Overflow;Stack Overflow;Stack Exchange	Multiple times per day	Yes	Multiple times per day	Neutral	25-34 years old	Man	No	Bisexual	White	None of the above	I have a mood or emotional disorder (e.g., depression, bipolar disorder, etc.);I have an anxiety disorder	No	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Appropriate in length	Neither easy nor difficult	40205.0
3	4	I am a developer by profession	Employed, full-time	Fully remote	I don’t code outside of work	Bachelor’s degree (B.A., B.S., B.Eng., etc.)	Books / Physical media;School (i.e., University, College, etc)	NaN	NaN	20.0	17.0	Developer, full-stack	100 to 499 employees	I have some influence	Other (please specify):	Israel	ILS\tIsraeli new shekel	60000.0	Monthly	C#;JavaScript;SQL;TypeScript	C#;SQL;TypeScript	Microsoft SQL Server	Microsoft SQL Server	NaN	NaN	ASP.NET;ASP.NET Core	ASP.NET;ASP.NET Core	.NET	.NET	NaN	NaN	Notepad++;Visual Studio;Visual Studio Code	Notepad++;Visual Studio;Visual Studio Code	Windows	Windows	Git	Code editor;Command-line;Version control hosting service web GUI;Dedicated version control GUI application	NaN	NaN	Jira Work Management;Trello	Jira Work Management;Trello	Slack;Zoom	Slack;Zoom	Very unfavorable	Collectives on Stack Overflow;Stack Overflow for Teams (private knowledge sharing & collaboration platform for companies);Stack Overflow;Stack Exchange	Daily or almost daily	Yes	A few times per week	Yes, definitely	35-44 years old	Man	No	Straight / Heterosexual	White	None of the above	None of the above	No	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Appropriate in length	Easy	215232.0
4	5	I am a developer by profession	Employed, full-time	Hybrid (some remote, some in-person)	Hobby	Bachelor’s degree (B.A., B.S., B.Eng., etc.)	Other online resources (e.g., videos, blogs, forum);School (i.e., University, College, etc);On the job training	Technical documentation;Blogs;Stack Overflow;Online books;Video-based Online Courses;Online challenges (e.g., daily or weekly coding challenges)	NaN	8.0	3.0	Developer, front-end;Developer, full-stack;Developer, back-end;Developer, desktop or enterprise applications;Developer, QA or test	20 to 99 employees	I have some influence	Start a free trial;Visit developer communities like Stack Overflow	United States of America	USD\tUnited States dollar	NaN	NaN	C#;HTML/CSS;JavaScript;SQL;Swift;TypeScript	C#;Elixir;F#;Go;JavaScript;Rust;TypeScript	Cloud Firestore;Elasticsearch;Microsoft SQL Server;Firebase Realtime Database	Cloud Firestore;Elasticsearch;Firebase Realtime Database;Redis	Firebase;Microsoft Azure	Firebase;Microsoft Azure	Angular;ASP.NET;ASP.NET Core ;jQuery;Node.js	Angular;ASP.NET Core ;Blazor;Node.js	.NET	.NET;Apache Kafka	npm	Docker;Kubernetes	Notepad++;Visual Studio;Visual Studio Code;Xcode	Rider;Visual Studio;Visual Studio Code	Windows	macOS;Windows	Git;Other (please specify):	Code editor	NaN	NaN	NaN	NaN	Microsoft Teams;Zoom	NaN	Unfavorable	Collectives on Stack Overflow;Stack Overflow for Teams (private knowledge sharing & collaboration platform for companies);Stack Overflow;Stack Exchange	Multiple times per day	Yes	Daily or almost daily	Yes, definitely	25-34 years old	NaN	NaN	NaN	NaN	NaN	NaN	No	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Too long	Easy	NaN
5	6	I am not primarily a developer, but I write code sometimes as part of my work	Student, full-time	NaN	NaN	Master’s degree (M.A., M.S., M.Eng., MBA, etc.)	Books / Physical media;School (i.e., University, College, etc)	NaN	NaN	15.0	NaN	NaN	NaN	NaN	Other (please specify):	Germany	NaN	NaN	NaN	C++;Lua	Lua	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Homebrew	Homebrew	Visual Studio Code;Xcode	Visual Studio Code	Linux-based;macOS	macOS	Git	Command-line;Version control hosting service web GUI;Dedicated version control GUI application	NaN	NaN	Confluence	NaN	Rocketchat;Slack;Zoom	Rocketchat;Slack;Zoom	Very unfavorable	Stack Overflow;Stack Exchange	Multiple times per day	Yes	Multiple times per day	Yes, definitely	25-34 years old	Or, in your own words:	Or, in your own words:	Prefer to self-describe:	Or, in your own words:	Or, in your own words:	Or, in your own words:	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Appropriate in length	Easy	NaN
6	7	I code primarily as a hobby	Student, part-time	NaN	NaN	Secondary school (e.g. American high school, German Realschule or Gymnasium, etc.)	Other online resources (e.g., videos, blogs, forum)	Stack Overflow;Video-based Online Courses	NaN	3.0	NaN	NaN	NaN	NaN	Start a free trial;Visit developer communities like Stack Overflow	India	NaN	NaN	NaN	C++;HTML/CSS;JavaScript;PHP;Python;TypeScript	C;C#;C++;Elixir;Go;HTML/CSS;Java;JavaScript;Kotlin;Python;Rust;Swift;TypeScript	Cloud Firestore;MongoDB;Firebase Realtime Database	MySQL;Oracle;PostgreSQL	NaN	NaN	Angular;Next.js;Node.js;React.js;Svelte;Vue.js	Django;Flask;Gatsby;jQuery;Next.js;Node.js;React.js;Svelte;Vue.js	NaN	NaN	Homebrew;npm	npm	Atom;IntelliJ;Notepad++;PyCharm;Sublime Text;Visual Studio Code	Visual Studio Code;Webstorm	macOS	macOS	Git	Code editor;Command-line	NaN	NaN	NaN	NaN	Google Chat;Microsoft Teams;Slack;Zoom	Google Chat;Slack;Zoom	Favorable	Stack Overflow	Multiple times per day	Yes	Daily or almost daily	Yes, definitely	Under 18 years old	Man	No	NaN	Indian	None of the above	None of the above	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Appropriate in length	Easy	NaN
7	8	I am a developer by profession	Not employed, but looking for work	NaN	NaN	Some college/university study without earning a degree	Online Courses or Certification	NaN	Coursera;Udemy	1.0	NaN	Developer, full-stack;Student	NaN	NaN	Start a free trial	India	NaN	NaN	NaN	C;C++;HTML/CSS;Java;JavaScript;SQL	APL;Bash/Shell;Go;Python;TypeScript	MongoDB;MySQL	Neo4j;PostgreSQL	AWS;Google Cloud;Heroku	DigitalOcean;Firebase;Microsoft Azure;VMware	jQuery;Node.js	Angular;Angular.js;Next.js;Vue.js	NaN	NaN	npm	Unity 3D;Yarn	Atom;CLion;Eclipse;IntelliJ;Notepad++;Visual Studio	Android Studio;IPython/Jupyter;Sublime Text;Vim;Visual Studio Code	Linux-based;macOS	Windows	Git	Command-line	NaN	NaN	NaN	NaN	Google Chat;Microsoft Teams;Zoom	NaN	Very favorable	Collectives on Stack Overflow;Stack Overflow;Stack Exchange	A few times per week	Yes	I have never participated in Q&A on Stack Overflow	Yes, definitely	18-24 years old	Man	No	Straight / Heterosexual	Indian	None of the above	None of the above	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Appropriate in length	Easy	NaN
8	9	I am a developer by profession	Employed, full-time	Hybrid (some remote, some in-person)	I don’t code outside of work	Master’s degree (M.A., M.S., M.Eng., MBA, etc.)	On the job training;Coding Bootcamp	NaN	NaN	6.0	6.0	Developer, back-end	I don’t know	I have little or no influence	NaN	Netherlands	EUR European Euro	46000.0	Yearly	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Emacs;Notepad++	Emacs;Notepad++	Windows	Windows	Git	Command-line;Dedicated version control GUI application	NaN	NaN	Confluence;Jira Work Management	Confluence;Jira Work Management	Microsoft Teams	Microsoft Teams	Very unfavorable	Stack Overflow for Teams (private knowledge sharing & collaboration platform for companies);Stack Overflow;Stack Exchange	A few times per month or weekly	Yes	Less than once per month or monthly	No, not at all	25-34 years old	Woman	No	Prefer to self-describe:	European	Or, in your own words:	Or, in your own words:	Yes	Independent contributor	6.0	Agree	Disagree	Agree	Agree	Agree	Agree	Disagree	3-5 times a week	3-5 times a week	Never	15-30 minutes a day	Over 120 minutes a day	Somewhat long	Innersource initiative;DevOps function;Microservices;Developer portal or other central places to find tools/services;Continuous integration (CI) and (more often) continuous delivery;Automated testing;Observability tools	Yes	Yes	Yes	Appropriate in length	Easy	49056.0
9	10	I am a developer by profession	Independent contractor, freelancer, or self-employed	Fully remote	Hobby;Contribute to open-source projects;Bootstrapping a business	Some college/university study without earning a degree	Books / Physical media;Other online resources (e.g., videos, blogs, forum);School (i.e., University, College, etc)	Technical documentation;Blogs;Written Tutorials;Stack Overflow;Online books;Online forum	NaN	37.0	30.0	Developer, desktop or enterprise applications;Developer, mobile;Educator	Just me - I am a freelancer, sole proprietor, etc.	I have a great deal of influence	Start a free trial;Ask developers I know/work with;Research companies that have advertised on sites I visit	Croatia	HRK\tCroatian kuna	NaN	NaN	Delphi;Java;Swift	Delphi;Java;Swift	NaN	NaN	DigitalOcean;Firebase	DigitalOcean;Firebase	NaN	NaN	NaN	NaN	NaN	NaN	Android Studio;RAD Studio (Delphi, C++ Builder);Visual Studio Code;Xcode	Android Studio;RAD Studio (Delphi, C++ Builder);Visual Studio Code;Xcode	Windows	Windows	Git	Version control hosting service web GUI;Dedicated version control GUI application	NaN	NaN	NaN	NaN	Google Chat;Slack	Google Chat;Slack	Very unfavorable	Collectives on Stack Overflow;Stack Overflow;Stack Exchange	Multiple times per day	Yes	Multiple times per day	Yes, definitely	45-54 years old	Woman	No	Straight / Heterosexual	White;European	None of the above	None of the above	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Appropriate in length	Easy	NaN

	ResponseId	MainBranch	Employment	RemoteWork	CodingActivities	EdLevel	LearnCode	LearnCodeOnline	LearnCodeCoursesCert	YearsCode	YearsCodePro	DevType	OrgSize	PurchaseInfluence	BuyNewTool	Country	Currency	CompTotal	CompFreq	LanguageHaveWorkedWith	LanguageWantToWorkWith	DatabaseHaveWorkedWith	DatabaseWantToWorkWith	PlatformHaveWorkedWith	PlatformWantToWorkWith	WebframeHaveWorkedWith	WebframeWantToWorkWith	MiscTechHaveWorkedWith	MiscTechWantToWorkWith	ToolsTechHaveWorkedWith	ToolsTechWantToWorkWith	NEWCollabToolsHaveWorkedWith	NEWCollabToolsWantToWorkWith	OpSysProfessional use	OpSysPersonal use	VersionControlSystem	VCInteraction	VCHostingPersonal use	VCHostingProfessional use	OfficeStackAsyncHaveWorkedWith	OfficeStackAsyncWantToWorkWith	OfficeStackSyncHaveWorkedWith	OfficeStackSyncWantToWorkWith	Blockchain	NEWSOSites	SOVisitFreq	SOAccount	SOPartFreq	SOComm	Age	Gender	Trans	Sexuality	Ethnicity	Accessibility	MentalHealth	TBranch	ICorPM	WorkExp	Knowledge_1	Knowledge_2	Knowledge_3	Knowledge_4	Knowledge_5	Knowledge_6	Knowledge_7	Frequency_1	Frequency_2	Frequency_3	TimeSearching	TimeAnswering	Onboarding	ProfessionalTech	TrueFalse_1	TrueFalse_2	TrueFalse_3	SurveyLength	SurveyEase	ConvertedCompYearly
40	41	I am a developer by profession	Employed, full-time	Hybrid (some remote, some in-person)	Hobby;Freelance/contract work	Associate degree (A.A., A.S., etc.)	Books / Physical media;Other online resources (e.g., videos, blogs, forum);School (i.e., University, College, etc)	Technical documentation;Blogs;Written Tutorials;Stack Overflow;Online forum;How-to videos	NaN	20.0	15.0	Developer, front-end;Engineer, data;Developer, full-stack;Developer, back-end;Developer, desktop or enterprise applications;Developer, QA or test;Developer, mobile;Database administrator;Developer, embedded applications or devices;Cloud infrastructure engineer;Data or business analyst;Designer	100 to 499 employees	I have a great deal of influence	Start a free trial;Visit developer communities like Stack Overflow;Ask developers I know/work with;Research companies that have advertised on sites I visit;Read ratings or reviews on third party sites like G2Crowd	United States of America	USD\tUnited States dollar	130000.0	Yearly	C#;C++;HTML/CSS;JavaScript;SQL;TypeScript;VBA	NaN	MongoDB;MySQL;SQLite	NaN	AWS;Managed Hosting;Microsoft Azure	NaN	ASP.NET;ASP.NET Core ;jQuery	NaN	.NET;Xamarin	NaN	NaN	NaN	Notepad++;Visual Studio;Visual Studio Code	NaN	NaN	macOS;Windows	Git	Code editor	NaN	NaN	NaN	NaN	NaN	NaN	Unsure	Stack Overflow;Stack Exchange	A few times per week	Yes	A few times per month or weekly	Yes, somewhat	35-44 years old	Man	No	Straight / Heterosexual	White	NaN	None of the above	No	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Appropriate in length	Easy	130000.0
41	42	I am a developer by profession	Employed, full-time	Hybrid (some remote, some in-person)	I don’t code outside of work	Secondary school (e.g. American high school, German Realschule or Gymnasium, etc.)	Other online resources (e.g., videos, blogs, forum);On the job training;Online Courses or Certification	Technical documentation;Blogs;Written Tutorials;Stack Overflow;Video-based Online Courses;Written-based Online Courses	Coursera;Udemy;Udacity	3.0	3.0	Data scientist or machine learning specialist;Engineer, data;Developer, back-end	20 to 99 employees	I have little or no influence	Visit developer communities like Stack Overflow;Ask developers I know/work with;Read ratings or reviews on third party sites like G2Crowd	Israel	ILS\tIsraeli new shekel	19000.0	Monthly	Bash/Shell;HTML/CSS;Python;SQL	Bash/Shell;Python;SQL	PostgreSQL	PostgreSQL;Redis	AWS;Google Cloud	AWS	NaN	NaN	Keras;NumPy;Pandas;Scikit-learn;TensorFlow	Keras;NumPy;Pandas;Scikit-learn;TensorFlow;Hugging Face Transformers	Docker	Docker	IPython/Jupyter;Vim	IPython/Jupyter;PyCharm;Vim	Linux-based	Windows	Git	Command-line	NaN	NaN	Confluence;Jira Work Management	Confluence;Jira Work Management	Slack	Slack	Indifferent	Stack Overflow;Stack Exchange	Daily or almost daily	No	NaN	No, not really	18-24 years old	Man	No	Straight / Heterosexual	Middle Eastern	None of the above	I have an anxiety disorder	Yes	Independent contributor	3.0	Agree	Neither agree nor disagree	Disagree	Agree	Agree	Agree	Neither agree nor disagree	1-2 times a week	10+ times a week	Never	30-60 minutes a day	15-30 minutes a day	Somewhat short	NaN	NaN	Yes	Yes	Appropriate in length	Neither easy nor difficult	68160.0
42	43	I am a developer by profession	Not employed, but looking for work	NaN	NaN	Bachelor’s degree (B.A., B.S., B.Eng., etc.)	Other online resources (e.g., videos, blogs, forum);School (i.e., University, College, etc);Online Courses or Certification;Colleague	Technical documentation;Blogs;Stack Overflow;Video-based Online Courses;How-to videos;Written-based Online Courses;Interactive tutorial;Coding sessions (live or recorded)	Udemy;Pluralsight	4.0	NaN	Developer, front-end;Developer, full-stack;Developer, back-end;Database administrator	NaN	NaN	Start a free trial;Visit developer communities like Stack Overflow;Ask developers I know/work with	Iraq	NaN	NaN	NaN	C#;HTML/CSS;JavaScript;PHP;Ruby;SQL	C#;HTML/CSS;JavaScript;Python;Ruby;SQL;TypeScript	Microsoft SQL Server;MongoDB;MySQL;Oracle;PostgreSQL	DynamoDB;Elasticsearch;Microsoft SQL Server;MongoDB;MySQL;PostgreSQL;Redis	AWS;Microsoft Azure	AWS;Heroku;Microsoft Azure	ASP.NET Core ;jQuery;Ruby on Rails	Angular;Angular.js;ASP.NET Core ;Blazor;Django;Node.js;React.js;Ruby on Rails	.NET	.NET;React Native	Docker;npm;Yarn	Docker	Eclipse;IntelliJ;NetBeans;Visual Studio;Visual Studio Code	Visual Studio;Visual Studio Code	Linux-based;Windows	Windows	Git	Code editor;Command-line	NaN	NaN	NaN	NaN	Microsoft Teams;Slack;Zoom	Microsoft Teams;Zoom	Very favorable	Stack Overflow;Stack Exchange	Daily or almost daily	Yes	I have never participated in Q&A on Stack Overflow	Neutral	25-34 years old	Man	No	Bisexual	Middle Eastern	None of the above	None of the above	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Appropriate in length	Easy	NaN
43	44	I code primarily as a hobby	Employed, full-time;Student, part-time	Full in-person	Hobby	Some college/university study without earning a degree	Books / Physical media;Other online resources (e.g., videos, blogs, forum)	Technical documentation;Written Tutorials;Stack Overflow	NaN	15.0	NaN	NaN	NaN	NaN	Other (please specify):;Visit developer communities like Stack Overflow	Sweden	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Node.js	NaN	NaN	NaN	npm	NaN	Nano;Notepad++;Vim;Visual Studio Code	Vim;Visual Studio Code	Linux-based	Linux-based	Git	Command-line	NaN	NaN	NaN	NaN	Slack	Slack	Favorable	Stack Overflow	A few times per month or weekly	Yes	I have never participated in Q&A on Stack Overflow	No, not at all	35-44 years old	Man	No	Bisexual;Straight / Heterosexual	European	None of the above	I have a mood or emotional disorder (e.g., depression, bipolar disorder, etc.);I have an anxiety disorder;I have a concentration and/or memory disorder (e.g., ADHD, etc.)	No	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Appropriate in length	Neither easy nor difficult	NaN
44	45	I am a developer by profession	Student, full-time	NaN	NaN	Secondary school (e.g. American high school, German Realschule or Gymnasium, etc.)	School (i.e., University, College, etc)	NaN	NaN	6.0	NaN	NaN	NaN	NaN	Start a free trial;Visit developer communities like Stack Overflow	Austria	NaN	NaN	NaN	Bash/Shell;HTML/CSS;Java;JavaScript;Kotlin;Python;R;SQL	Bash/Shell;Java;Kotlin;SQL	MySQL	MySQL	NaN	NaN	ASP.NET;ASP.NET Core	NaN	.NET;NumPy;Spring;Torch/PyTorch	NumPy;Spring;TensorFlow;Torch/PyTorch	Docker	Docker	Eclipse;IntelliJ;PyCharm	Eclipse;IntelliJ;PyCharm	Windows	Linux-based;Windows;Windows Subsystem for Linux (WSL)	Git	Command-line	NaN	NaN	NaN	NaN	Microsoft Teams;Zoom	NaN	Unsure	Collectives on Stack Overflow;Stack Overflow for Teams (private knowledge sharing & collaboration platform for companies);Stack Overflow;Stack Exchange	Multiple times per day	Yes	A few times per week	Yes, definitely	18-24 years old	Man	No	Straight / Heterosexual	White;European	None of the above	None of the above	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Appropriate in length	Easy	NaN
45	46	I am a developer by profession	Employed, full-time	Hybrid (some remote, some in-person)	Other (please specify):	Master’s degree (M.A., M.S., M.Eng., MBA, etc.)	Other online resources (e.g., videos, blogs, forum);Online Courses or Certification	Technical documentation;Video-based Online Courses;How-to videos	Udemy	4.0	3.0	Developer, front-end	500 to 999 employees	I have little or no influence	Start a free trial	Madagascar	EUR European Euro	400.0	Monthly	JavaScript;TypeScript	Dart	MongoDB;MySQL	MongoDB;MySQL;PostgreSQL;Firebase Realtime Database	NaN	NaN	Node.js;React.js;Vue.js	Node.js;React.js;Vue.js	React Native	Flutter	npm;Yarn	Docker;npm;Yarn	Visual Studio Code	Visual Studio Code	NaN	Windows	Git	Command-line	NaN	NaN	NaN	NaN	NaN	NaN	Favorable	Stack Overflow	A few times per month or weekly	Yes	I have never participated in Q&A on Stack Overflow	No, not really	25-34 years old	Man	No	Straight / Heterosexual	African	None of the above	None of the above	Yes	Independent contributor	3.0	Strongly agree	Agree	Agree	Strongly agree	Strongly agree	Strongly agree	Agree	1-2 times a week	1-2 times a week	Never	Less than 15 minutes a day	15-30 minutes a day	Very long	Microservices	No	Yes	Yes	Too long	Easy	5124.0
46	47	I code primarily as a hobby	Student, full-time	NaN	NaN	Secondary school (e.g. American high school, German Realschule or Gymnasium, etc.)	Other online resources (e.g., videos, blogs, forum);Other (please specify):	Technical documentation;Blogs;How-to videos	NaN	7.0	NaN	NaN	NaN	NaN	Other (please specify):	Norway	NaN	NaN	NaN	Bash/Shell;C;C++;Java;Lua;Python	Bash/Shell;C++;Lua;Python	MongoDB;SQLite	SQLite	NaN	NaN	Node.js;React.js	NaN	NaN	NaN	npm	NaN	Eclipse;IntelliJ;Vim	Vim	Linux-based	Linux-based	Git	Command-line	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Collectives on Stack Overflow;Stack Overflow for Teams (private knowledge sharing & collaboration platform for companies);Stack Overflow;Stack Exchange	Multiple times per day	Yes	Multiple times per day	Yes, definitely	18-24 years old	Woman	Yes	Prefer to self-describe:	White;European	None of the above	I have autism / an autism spectrum disorder (e.g. Asperger's, etc.)	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Too short	Neither easy nor difficult	NaN
47	48	I am a developer by profession	Employed, full-time	Fully remote	Hobby	Bachelor’s degree (B.A., B.S., B.Eng., etc.)	Friend or family member;Other online resources (e.g., videos, blogs, forum);School (i.e., University, College, etc)	Technical documentation;Blogs;Written Tutorials;Stack Overflow;Online books;Video-based Online Courses;Online challenges (e.g., daily or weekly coding challenges);Online forum;How-to videos;Written-based Online Courses;Interactive tutorial	NaN	6.0	5.0	Developer, full-stack;Developer, back-end	1,000 to 4,999 employees	I have little or no influence	Start a free trial;Visit developer communities like Stack Overflow;Ask developers I know/work with	United States of America	USD\tUnited States dollar	135000.0	Yearly	Java;JavaScript;PHP;SQL;TypeScript	C++;Go	Cassandra;MySQL	NaN	NaN	NaN	Angular;Angular.js;jQuery	NaN	NaN	NaN	Docker;Homebrew;Kubernetes;npm;Yarn	NaN	CLion;IntelliJ;PhpStorm	NaN	macOS	macOS	Git	Command-line	NaN	NaN	Confluence;Jira Work Management	NaN	Slack;Zoom	NaN	Indifferent	Stack Overflow;Stack Exchange	Daily or almost daily	No	NaN	No, not really	25-34 years old	Woman	No	Straight / Heterosexual	White;European;Asian;East Asian	None of the above	I have an anxiety disorder	Yes	Independent contributor	5.0	Strongly agree	Agree	Disagree	Disagree	Agree	Agree	Agree	1-2 times a week	6-10 times a week	1-2 times a week	30-60 minutes a day	30-60 minutes a day	Somewhat long	DevOps function;Microservices;Developer portal or other central places to find tools/services;Automated testing;Observability tools	Yes	Yes	Yes	Appropriate in length	Easy	135000.0
48	49	I am a developer by profession	Employed, full-time	Hybrid (some remote, some in-person)	Hobby;Contribute to open-source projects	Some college/university study without earning a degree	Books / Physical media;Other online resources (e.g., videos, blogs, forum);School (i.e., University, College, etc)	Technical documentation;Blogs;Written Tutorials;Stack Overflow	NaN	40.0	25.0	Developer, back-end;Developer, desktop or enterprise applications	20 to 99 employees	I have some influence	Start a free trial;Visit developer communities like Stack Overflow	Germany	EUR European Euro	100000.0	Yearly	Haskell;Java;Rust	Dart;Haskell;Java;Swift	PostgreSQL	NaN	NaN	NaN	NaN	NaN	.NET	Flutter	NaN	NaN	Emacs;IntelliJ;Notepad++;Vim;Visual Studio	Android Studio;Emacs;IntelliJ;Notepad++;Vim;Visual Studio;Xcode	Windows;Windows Subsystem for Linux (WSL)	Linux-based;macOS	Git	Code editor;Command-line;Version control hosting service web GUI	NaN	NaN	NaN	NaN	Microsoft Teams	Microsoft Teams	Very unfavorable	Stack Overflow;Stack Exchange	Daily or almost daily	Yes	A few times per month or weekly	Yes, somewhat	55-64 years old	Man	No	Straight / Heterosexual	European	None of the above	None of the above	Yes	NaN	28.0	Strongly agree	Disagree	Neither agree nor disagree	Disagree	Disagree	Agree	Disagree	1-2 times a week	3-5 times a week	Never	15-30 minutes a day	Less than 15 minutes a day	Just right	Continuous integration (CI) and (more often) continuous delivery;Automated testing	Yes	No	Yes	Appropriate in length	Easy	106644.0
49	50	I am a developer by profession	Employed, full-time	Fully remote	Hobby	Secondary school (e.g. American high school, German Realschule or Gymnasium, etc.)	Other online resources (e.g., videos, blogs, forum);School (i.e., University, College, etc)	Technical documentation;Blogs;Stack Overflow	NaN	7.0	4.0	Developer, front-end;Developer, full-stack;Developer, back-end;DevOps specialist;Cloud infrastructure engineer	100 to 499 employees	I have some influence	Visit developer communities like Stack Overflow	Germany	EUR European Euro	4000.0	Monthly	C#;HTML/CSS;JavaScript;SQL;TypeScript	C#;HTML/CSS;JavaScript;SQL;TypeScript	PostgreSQL	Elasticsearch;PostgreSQL	NaN	NaN	Angular;ASP.NET Core	Angular;ASP.NET Core	NaN	NaN	Ansible;Docker;npm	Ansible;Docker;npm	Nano;Rider;Visual Studio Code;Webstorm	Rider;Vim;Visual Studio Code;Webstorm	Linux-based	Linux-based;Windows	Git	Code editor;Command-line;Version control hosting service web GUI	NaN	NaN	Jira Work Management	NaN	Microsoft Teams	NaN	Indifferent	Collectives on Stack Overflow;Stack Overflow;Stack Exchange	Multiple times per day	Yes	I have never participated in Q&A on Stack Overflow	Neutral	25-34 years old	Man	No	Bisexual	White;European	None of the above	NaN	Yes	Independent contributor	7.0	Neither agree nor disagree	Agree	Agree	Agree	Strongly agree	Agree	Disagree	Never	1-2 times a week	1-2 times a week	30-60 minutes a day	15-30 minutes a day	Somewhat long	Continuous integration (CI) and (more often) continuous delivery;Automated testing;Observability tools	No	No	Yes	Appropriate in length	Easy	51192.0

Overview

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Common Values

Length

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Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Other Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Other Punctuation

Space Separator

Dash Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Dash Punctuation

Open Punctuation

Other Punctuation

Close Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Other Punctuation

Space Separator

Final Punctuation

Dash Punctuation

Open Punctuation

Close Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Punctuation

Common Values

Length